CNVRanger: association analysis of CNVs with gene expression and quantitative phenotypes

High level of aneuploidy and recurrent loss of chromosome 11 as relevant features of somatotroph pituitary tumors

BACKGROUND

Somatotroph neuroendocrine pituitary tumors (sPitNET) are a subtype of pituitary tumors that commonly cause acromegaly. Our study aimed to determine the spectrum of DNA copy number abnormalities (CNAs) in sPitNETs and their relevance.

METHODS

A landscape of CNAs in sPitNETs was determined using combined whole-genome approaches involving low-pass whole genome sequencing and SNP microarrays. Fluorescent in situ hybridization (FISH) was used for microscopic validation of CNAs. The tumors were also subjected to transcriptome and DNA methylation analyses with RNAseq and microarrays, respectively.

RESULTS

We observed a wide spectrum of cytogenetic changes ranging from multiple deletions, recurrent chromosome 11 loss, stable genomes, to duplication of the majority of the chromosomes. The identified CNAs were confirmed with FISH. sPitNETs with multiple duplications were characterized by intratumoral heterogeneity in chromosome number variation in individual tumor cells, as determined with FISH. These tumors were separate CNA-related sPitNET subtype in clustering analyses with CNA signature specific for whole genome doubling-related etiology. This subtype encompassed GNAS-wild type, mostly densely granulated tumors with favorable expression level of known prognosis-related genes, notably enriched with POUF1/NR5A1-double positive PitNETs. Chromosomal deletions in sPitNETs are functionally relevant. They occurred in gene-dense DNA regions and were related to genes downregulation and increased DNA methylation in the CpG island and promoter regions in the affected regions. Recurrent loss of chromosome 11 was reflected by lowered MEN1 and AIP. No such unequivocal relevance was found for chromosomal gains. Comparisons of transcriptomes of selected most cytogenetically stable sPitNETs with tumors with recurrent loss of chromosome 11 showed upregulation of processes related to gene dosage compensation mechanism in tumors with deletion. Comparison of stable tumors with those with multiple duplications showed upregulation of processes related to mitotic spindle, DNA repair, and chromatin organization. Both comparisons showed upregulation of the processes related to immune infiltration in cytogenetically stable tumors and deconvolution of DNA methylation data indicated a higher content of specified immune cells and lower tumor purity in these tumors.

CONCLUSIONS

sPitNETs fall into three relevant cytogenetic groups: highly aneuploid tumors characterized by known prognostically favorable features and low aneuploidy tumors including specific subtype with chromosome 11 loss.

Genome-wide copy number variant analysis reveals candidate genes associated with milk production traits in water buffalo (Bubalus bubalis)

Buffaloes are vital contributors to the global dairy industry. Understanding the genetic basis of milk production traits in buffalo populations is essential for breeding programs and improving productivity. In this study, we conducted whole-genome resequencing on 387 buffalo genomes from 29 diverse Asian breeds, including 132 river buffaloes, 129 swamp buffaloes, and 126 crossbred buffaloes. We identified 36,548 copy number variants (CNV) spanning 133.29 Mb of the buffalo genome, resulting in 2,100 CNV regions (CNVR), with 1,993 shared CNVR being found within the studied buffalo types. Analyzing CNVR highlighted distinct genetic differentiation between river and swamp buffalo subspecies, verified by evolutionary tree and principal component analyses. Admixture analysis grouped buffaloes into river and swamp categories, with crossbred buffaloes displaying mixed ancestry. To identify candidate genes associated with milk production traits, we employed 3 approaches. First, we used Vst-based population differentiation, revealing 11 genes within CNVR that exhibited significant divergence between different buffalo breeds, including genes linked to milk production traits. Second, expression quantitative loci analysis revealed differentially expressed CNVR-derived genes (DECG) associated with milk production traits. Notably, known milk production-related genes were among these DECG, validating their relevance. Last, a GWAS identified 3 CNVR significantly linked to peak milk yield. Our study provides comprehensive genomic insights into buffalo populations and identifies candidate genes associated with milk production traits. These findings facilitate genetic breeding programs aimed at increasing milk yield and improving quality in this economically important livestock species.

Genome wide detection of CNV and their association with body size in Danzhou chickens

Copy number variation (CNV) is a crucial component of genetic diversity in the genome, serving as the foundation for the genetic architecture and phenotypic variability of complex traits. In this study, we examined CNVs in the Danzhou (DZ) chicken, an indigenous breed exclusive to Hainan Province, China. By employing whole-genome resequencing data from 200 DZ chickens, we conducted a comprehensive genome-wide analysis of CNVs using CNVpytor and performed CNV-based genome-wide association studies (GWAS) on 6 body size traits, including body slope length (BSL), keel length (KeL), tibial length (TiL), tibial circumference (TiC), chest width (ChW), and chest depth (ChD) utilizing linear mixed model methods considering a genomic relationship matrix. We identified a total of 144,265 autosomal CNVs among the 200 individuals, comprising 67,818 deletions and 76,447 duplications. After merging these variants together, we obtained 4,824 distinct copy number variant regions, which accounted for approximately 20% of the chicken autosomal genome. Furthermore, we discovered several significantly associated CNV segments with body size traits located proximal to genes such as IHH, WNT6, WNT10A, LPR4, FZD2, WNT7B, and GNAS that have been extensively implicated in skeletal development and growth processes. These findings enhance our understanding of CNVs in chickens and their potential impact on body size traits by revealing candidate genes involved in the regulation of these traits. This establishes a solid framework for future studies and may prove particularly beneficial for exploring genetic structural variation in chickens.

Genome-wide association study of copy number variations with shank traits in a F2 crossbred chicken population

Copy number variations (CNVs) are large-scale changes in the DNA sequence that can affect the genetic structure and phenotype of an organism. The purpose of this study was to investigate the existing CNVs and their associations with the shank diameter (ShD) and shank length (ShL) traits using data from an F2 crossbred chicken population. To carry out the study, 312 chickens were genotyped using the Illumina 60k SNP Beadchip. The shank traits of the birds were measured from day 1 to 12 weeks of age. penncnv and cnvruler tools were used to find copy numbers and regions with copy number changes (CNVR), respectively. The CNVRanger package was used to perform a genome-wide association study between shank traits and CNVs. Gene ontology research in CNVRs was carried out using the david database. In this investigation, 966 CNVs and 606 regions with copy number changes were discovered. The copy number states and variations were randomly distributed along the length of the autosomal chromosomes. Weeks 1-4, 9 and 12 of growth revealed a significant association of copy number variations with shank traits, false discovery rate (FDR-corrected p-value < 0.01), and the majority of CNVs that were statistically significant were found on chromosomes 1-3. These CNV segments are nearby genes such as KCNJ12, FGF6 and MYF5, which are fundamental to growth and development. In addition, gene set analyses revealed terms related to muscle physiology, regulation of cellular processes and potassium channels.

Common genetic variants associated with urinary phthalate levels in children: A genome-wide study

INTRODUCTION

Phthalates, or dieters of phthalic acid, are a ubiquitous type of plasticizer used in a variety of common consumer and industrial products. They act as endocrine disruptors and are associated with increased risk for several diseases. Once in the body, phthalates are metabolized through partially known mechanisms, involving phase I and phase II enzymes.

OBJECTIVE

In this study we aimed to identify common single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) associated with the metabolism of phthalate compounds in children through genome-wide association studies (GWAS).

METHODS

The study used data from 1,044 children with European ancestry from the Human Early Life Exposome (HELIX) cohort. Ten phthalate metabolites were assessed in a two-void pooled urine collected at the mean age of 8 years. Six ratios between secondary and primary phthalate metabolites were calculated. Genome-wide genotyping was done with the Infinium Global Screening Array (GSA) and imputation with the Haplotype Reference Consortium (HRC) panel. PennCNV was used to estimate copy number variants (CNVs) and CNVRanger to identify consensus regions. GWAS of SNPs and CNVs were conducted using PLINK and SNPassoc, respectively. Subsequently, functional annotation of suggestive SNPs (p-value < 1E-05) was done with the FUMA web-tool.

RESULTS

We identified four genome-wide significant (p-value < 5E-08) loci at chromosome (chr) 3 (FECHP1 for oxo-MiNP_oh-MiNP ratio), chr6 (SLC17A1 for MECPP_MEHHP ratio), chr9 (RAPGEF1 for MBzP), and chr10 (CYP2C9 for MECPP_MEHHP ratio). Moreover, 115 additional loci were found at suggestive significance (p-value < 1E-05). Two CNVs located at chr11 (MRGPRX1 for oh-MiNP and SLC35F2 for MEP) were also identified. Functional annotation pointed to genes involved in phase I and phase II detoxification, molecular transfer across membranes, and renal excretion.

CONCLUSION

Through genome-wide screenings we identified known and novel loci implicated in phthalate metabolism in children. Genes annotated to these loci participate in detoxification, transmembrane transfer, and renal excretion.

Unveiling the Influence of Copy Number Variations on Genetic Diversity and Adaptive Evolution in China's Native Pig Breeds via Whole-Genome Resequencing

Copy number variations (CNVs) critically influence individual genetic diversity and phenotypic traits. In this study, we employed whole-genome resequencing technology to conduct an in-depth analysis of 50 pigs from five local swine populations [Rongchang pig (RC), Wuzhishan pig (WZS), Tibetan pig (T), Yorkshire (YL) and Landrace (LR)], aiming to assess their genetic potential and explore their prospects in the field of animal model applications. We identified a total of 96,466 CNVs, which were subsequently integrated into 7112 non-redundant CNVRs, encompassing 1.3% of the swine genome. Functional enrichment analysis of the genes within these CNVRs revealed significant associations with sensory perception, energy metabolism, and neural-related pathways. Further selective scan analyses of the local pig breeds RC, T, WZS, along with YL and LR, uncovered that for the RC variety, the genes PLA2G10 and ABCA8 were found to be closely related to fat metabolism and cardiovascular health. In the T breed, the genes NCF2 and CSGALNACT1 were associated with immune response and connective tissue characteristics. As for the WZS breed, the genes PLIN4 and CPB2 were primarily linked to fat storage and anti-inflammatory responses. In summary, this research underscores the pivotal role of CNVs in fostering the diversity and adaptive evolution of pig breeds while also offering valuable insights for further exploration of the advantageous genetic traits inherent to China's local pig breeds. This facilitates the creation of experimental animal models tailored to the specific characteristics of these breeds, contributing to the advancement of livestock and biomedical research.

Genomic landscape and distinct molecular subtypes of primary testicular lymphoma

Primary testicular lymphoma (PTL) is a rare lymphoma predominantly occurring in the elderly male population. It is characterized by a limited response to treatment and a heightened tendency towards relapse. Histologically, approximately 90% of PTL cases are classified as diffuse large B-cell lymphomas (DLBCL). Genetic features of PTL were delineated in a limited scope within several independent studies. Some of the articles which analyzed the genetic characterization of DLBCL have incorporated PTL samples, but these have been constrained by small sample sizes. In addition, there have been an absence of independent molecular typing studies of PTL. This report summarizes the common mutational features, copy number variations (CNVs) and molecular typing of PTL patients, based on whole-exome sequencing (WES) conducted on a cohort of 25 PTL patients. Among them, HLA, CDKN2A and MYD88 had a high mutation frequency. In addition, we found two core mutational characteristics in PTL including mutation in genes linked to genomic instability (TP53 and CDKN2A) and mutation in immune-related genes (HLA, MYD88, CD79B). We performed molecular typing of 25 PTL patients into C1 subtype with predominantly TP53 mutations and C2 subtype with predominantly HLA mutations. Notably, mutations in the TP53 gene predicted a poor outcome in most types of lymphomas. However, the C1 subtype, dominated by TP53 mutations, had a better prognosis compared to the C2 subtype in PTL. C2 subtype exhibited a worse prognosis, aligning with our finding that the mechanism of immune escape in PTL was primarily the deletions of HLA rather than PD-L1/PD-L2 alterations, a contrast to other DLBCLs. Moreover, we calculated the tumor mutation burden (TMB) and identified that TMB can predict prognosis and recurrence rate in PTL. Our study underscores the significance of molecular typing in PTL based on mutational characteristics, which plays a crucial role in prognostication and guiding therapeutic strategies for patients.

The detection efficacy of noninvasive prenatal genetic testing (NIPT) for sex chromosome abnormalities and copy number variation and its differentiation in pregnant women of different ages

Objective

To analyze the efficacy of noninvasive prenatal genetic testing (NIPT) in detecting fetal sex chromosome abnormalities and copy number variation (CNV), compare the efficacy between NIPT and serological screening alone, and further analyze the fetal sex chromosome abnormalities and CNV differentiation in pregnant women of different ages, so as to provide a reference for the prevention and control of fetal birth defects.

Methods

Clinical data from 22,692 pregnant women admitted to our hospital from January 2013 to December 2022 were retrospectively analyzed. All participants underwent serological screening and NIPT screening to compare fetal chromosomal abnormalities between the two screening modalities. 145 women whose fetus were diagnosed as sex chromosome abnormalities and 36 women whose fetus were diagnosed as CNV abnormalities based on NIPT screening were selected for prenatal diagnosis by amniocentesis or karyotyping. Taking prenatal diagnosis as the standard, the four-grid table method was used to detect the positive predictive value of NIPT screening for fetal sex chromosomal abnormalities and CNV. According to the age, pregnant women were divided into 18-30 years old (n = 9844), 31-35 years old (n = 7612), >35 years old (n = 5236), and then the detection rates of sexual fetal chromosomal abnormalities, CNV and total chromosomal abnormalities were compared in pregnant women.

Results

Among the 22,692 pregnant women in this study, the high-risk proportion of serologic screening with 4.38% was higher than that of NIPT screening with 1.93% (P < 0.05). Among the 145 women with fetal sex chromosome abnormalities screened by NIPT, 122 cases of fetal sex chromosome abnormalities were diagnosed prenatally, including 45, X/47, XXX/47, XYY/47, XXY. The positive predictive values of NIPT screening were 25.00%, 58.82%, 85.71%, and 85.71%, respectively, with an overall predictive value of 44.26%. The positive predictive value of fetal sex chromosome abnormalities in NIPT screening was higher than that of serological screening (P < 0.05). Among the 36 pregnant women with fetal CNV, NIPT screening showed that CNVs≤10 Mb and CNVs>10 Mb were 33.33% and 66.67%, respectively. There were 12 cases of prenatal diagnosis of fetal CNV, among which the NIPT-screened positive predictive values of fetal copy number deletion, duplicate, deletion and duplicate were 50.00%, 57.14% and 100.00%, respectively, with an overall predictive value of 58.33%. The positive predictive value of CNV in NIPT screening was higher than that of serological screening without statistically significant difference (P > 0.05). The results of NIPT screening showed that the detection rate of fetal sex chromosome abnormalities and total abnormalities of pregnant women over 35 years of age was significantly higher than that of pregnant women aged 18-30 and 31-35 years (P < 0.05).

Conclusion

NIPT screening could greatly improve the detection efficacy of fetal sex chromosome abnormalities, CNV and other chromosome abnormalities, and decline the false positive rate. However, the positive predictive value of NIPT screening was relatively low, and further prenatal testing and genetic counseling are still required. In addition, NIPT screening for fetal sex chromosome abnormalities, and the detection rate of total abnormalities in pregnant women older than 35 years old were increased significantly, and pregnancy at an advanced age may be one of the risk factors for fetal chromosomal abnormalities.

Pituitary neuroendocrine tumors with PIT1/SF1 co-expression show distinct clinicopathological and molecular features

Pituitary neuroendocrine tumors (PitNETs) are classified according to cell lineage, which requires immunohistochemistry for adenohypophyseal hormones and the transcription factors (TFs) PIT1, SF1, and TPIT. According to the current WHO 2022 classification, PitNETs with co-expression of multiple TFs are termed "plurihormonal". Previously, PIT1/SF1 co-expression was prevailingly reported in PitNETs, which otherwise correspond to the somatotroph lineage. However, little is known about such tumors and the WHO classification has not recognized their significance. We compiled an in-house case series of 100 tumors, previously diagnosed as somatotroph PitNETs. Following TF staining, histopathological features associated with PIT1/SF1 co-expression were assessed. Integration of in-house and publicly available sample data allowed for a meta-analysis of SF1-associated clinicopathological and molecular features across a total of 270 somatotroph PitNETs. The majority (74%, 52/70) of our densely granulated somatotroph PitNETs (DGST) unequivocally co-expressed PIT1 and SF1 (DGST-PIT1/SF1). None (0%, 0/30) of our sparsely granulated somatotroph PitNETs (SGST) stained positive for SF1 (SGST-PIT1). Among DGST, PIT1/SF1 co-expression was significantly associated with scarce FSH/LH expression and fewer fibrous bodies compared to DGST-PIT1. Integrated molecular analyses including publicly available samples confirmed that DGST-PIT1/SF1, DGST-PIT1 and SGST-PIT1 represent distinct tumor subtypes. Clinicopathological meta-analyses indicated that DGST-PIT1 respond more favorably towards treatment with somatostatin analogs compared to DGST-PIT1/SF1, while both these subtypes show an overall less aggressive clinical course than SGST-PIT1. In this study, we spotlight that DGST with co-expression of PIT1 and SF1 represent a common, yet underrecognized, distinct PitNET subtype. Our study questions the rationale of generally classifying such tumors as "plurihormonal", and calls for a refinement of the WHO classification. We propose the term "somatogonadotroph PitNET".

Finding Predictors of Leg Defects in Pigs Using CNV-GWAS

One of the most important areas of modern genome research is the search for meaningful relationships between genetic variants and phenotypes. In the livestock field, there has been research demonstrating the influence of copy number variants (CNVs) on phenotypic variation. Despite the wide range in the number and size of detected CNVs, a significant proportion differ between breeds and their functional effects are underestimated in the pig industry. In this work, we focused on the problem of leg defects in pigs (lumps/growths in the area of the hock joint on the hind legs) and focused on searching for molecular genetic predictors associated with this trait for the selection of breeding stock. The study was conducted on Large White pigs using three CNV calling tools (PennCNV, QuantiSNP and R-GADA) and the CNVRanger association analysis tool (CNV-GWAS). As a result, the analysis identified three candidate CNVRs associated with the formation of limb defects. Subsequent functional analysis suggested that all identified CNVs may act as potential predictors of the hock joint phenotype of pigs. It should be noted that the results obtained indicate that all significant regions are localized in genes (CTH, SRSF11, MAN1A1 and LPIN1) responsible for the metabolism of amino acids, fatty acids, glycerolipids and glycerophospholipids, thereby related to the immune response, liver functions, content intramuscular fat and animal fatness. These results are consistent with previously published studies, according to which a predisposition to the formation of leg defects can be realized through genetic variants associated with the functions of the liver, kidneys and hematological characteristics.

Genetic Association Analysis of Copy Number Variations for Meat Quality in Beef Cattle

Meat quality is an economically important trait for global food production. Copy number variations (CNVs) have been previously implicated in elucidating the genetic basis of complex traits. In this article, we detected a total of 112,198 CNVs and 10,102 CNV regions (CNVRs) based on the Bovine HD SNP array. Next, we performed a CNV-based genome-wide association analysis (GWAS) of six meat quality traits and identified 12 significant CNV segments corresponding to eight candidate genes, including PCDH15, CSMD3, etc. Using region-based association analysis, we further identified six CNV segments relevant to meat quality in beef cattle. Among these, TRIM77 and TRIM64 within CNVR4 on BTA29 were detected as candidate genes for backfat thickness (BFT). Notably, we identified a 34 kb duplication for meat color (MC) which was supported by read-depth signals, and this duplication was embedded within the keratin gene family including KRT4, KRT78, and KRT79. Our findings will help to dissect the genetic architecture of meat quality traits from the aspects of CNVs, and subsequently improve the selection process in breeding programs.

Somatic mutations reveal hyperactive Notch signaling and racial disparities in prurigo nodularis

Prurigo nodularis (PN) is a chronic inflammatory skin disease that disproportionately affects African Americans and is characterized by pruritic skin nodules of unknown etiology. Little is known about genetic alterations in PN pathogenesis, especially relating to somatic events which are often implicated in inflammatory conditions. We thus performed whole-exome sequencing on 54 lesional and nonlesional skin biopsies from 17 PN patients and 10 atopic dermatitis (AD) patients for comparison. Somatic mutational analysis revealed that PN lesional skin harbors pervasive somatic mutations in fibrotic, neurotropic, and cancer-associated genes. Nonsynonymous mutations were most frequent in NOTCH1 and the Notch signaling pathway, a regulator of cellular proliferation and tissue fibrosis, and NOTCH1 mutations were absent in AD. Somatic copy-number analysis, combined with expression data, showed that recurrently deleted and downregulated genes in PN lesional skin are associated with axonal guidance and extension. Follow-up immunofluorescence validation demonstrated increased NOTCH1 expression in PN lesional skin fibroblasts and increased Notch signaling in PN lesional dermis. Finally, multi-center data revealed a significantly increased risk of NOTCH1-associated diseases in PN patients. In characterizing the somatic landscape of PN, we uncover novel insights into its pathophysiology and identify a role for dysregulated Notch signaling in PN.

Copy Number Variation on ABCC2-DNMBP Loci Affects the Diversity and Composition of the Fecal Microbiota in Pigs

Genetic variation in the pig genome partially modulates the composition of porcine gut microbial communities. Previous studies have been focused on the association between single nucleotide polymorphisms (SNPs) and the gut microbiota, but little is known about the relationship between structural variants and fecal microbial traits. The main goal of this study was to explore the association between porcine genome copy number variants (CNVs) and the diversity and composition of pig fecal microbiota. For this purpose, we used whole-genome sequencing data to undertake a comprehensive identification of CNVs followed by a genome-wide association analysis between the estimated CNV status and the fecal bacterial diversity in a commercial Duroc pig population. A CNV predicted as gain (DUP) partially harboring ABCC2-DNMBP loci was associated with richness (P = 5.41 × 10-5, false discovery rate [FDR] = 0.022) and Shannon α-diversity (P = 1.42 × 10-4, FDR = 0.057). The in silico predicted gain of copies was validated by real-time quantitative PCR (qPCR), and its segregation, and positive association with the richness and Shannon α-diversity of the porcine fecal bacterial ecosystem was confirmed in an unrelated F1 (Duroc × Iberian) cross. Our results advise the relevance of considering the role of host-genome structural variants as potential modulators of microbial ecosystems and suggest the ABCC2-DNMBP CNV as a host-genetic factor for the modulation of the diversity and composition of the fecal microbiota in pigs. IMPORTANCE A better understanding of the environmental and host factors modulating gut microbiomes is a topic of greatest interest. Recent evidence suggests that genetic variation in the pig genome partially controls the composition of porcine gut microbiota. However, since previous studies have been focused on the association between single nucleotide polymorphisms and the fecal microbiota, little is known about the relationship between other sources of genetic variation, like the structural variants and microbial traits. Here, we identified, experimentally validated, and replicated in an independent population a positive link between the gain of copies of ABCC2-DNMBP loci and the diversity and composition of pig fecal microbiota. Our results advise the relevance of considering the role of host-genome structural variants as putative modulators of microbial ecosystems and open the possibility of implementing novel holobiont-based management strategies in breeding programs for the simultaneous improvement of microbial traits and host performance.

Curated single cell multimodal landmark datasets for R/Bioconductor

BACKGROUND

The majority of high-throughput single-cell molecular profiling methods quantify RNA expression; however, recent multimodal profiling methods add simultaneous measurement of genomic, proteomic, epigenetic, and/or spatial information on the same cells. The development of new statistical and computational methods in Bioconductor for such data will be facilitated by easy availability of landmark datasets using standard data classes.

RESULTS

We collected, processed, and packaged publicly available landmark datasets from important single-cell multimodal protocols, including CITE-Seq, ECCITE-Seq, SCoPE2, scNMT, 10X Multiome, seqFISH, and G&T. We integrate data modalities via the MultiAssayExperiment Bioconductor class, document and re-distribute datasets as the SingleCellMultiModal package in Bioconductor's Cloud-based ExperimentHub. The result is single-command actualization of landmark datasets from seven single-cell multimodal data generation technologies, without need for further data processing or wrangling in order to analyze and develop methods within Bioconductor's ecosystem of hundreds of packages for single-cell and multimodal data.

CONCLUSIONS

We provide two examples of integrative analyses that are greatly simplified by SingleCellMultiModal. The package will facilitate development of bioinformatic and statistical methods in Bioconductor to meet the challenges of integrating molecular layers and analyzing phenotypic outputs including cell differentiation, activity, and disease.

RaggedExperiment: the missing link between genomic ranges and matrices in Bioconductor

SUMMARY

The RaggedExperiment R / Bioconductor package provides lossless representation of disparate genomic ranges across multiple specimens or cells, in conjunction with efficient and flexible calculations of rectangular-shaped summaries for downstream analysis. Applications include statistical analysis of somatic mutations, copy number, methylation, and open chromatin data. RaggedExperiment is compatible with multimodal data analysis as a component of MultiAssayExperiment data objects, and simplifies data representation and transformation for software developers and analysts.

MOTIVATION AND RESULTS

Measurement of copy number, mutation, single nucleotide polymorphism, and other genomic attributes that may be stored as VCF files produce "ragged" genomic ranges data: i.e. across different genomic coordinates in each sample. Ragged data are not rectangular or matrix-like, presenting informatics challenges for downstream statistical analyses. We present the RaggedExperiment R/Bioconductor data structure for lossless representation of ragged genomic data, with associated reshaping tools for flexible and efficient calculation of tabular representations to support a wide range of downstream statistical analyses. We demonstrate its applicability to copy number and somatic mutation data across 33 TCGA cancer datasets.

MethylMasteR: A Comparison and Customization of Methylation-Based Copy Number Variation Calling Software in Cancers Harboring Large Scale Chromosomal Deletions

DNA methylation-based copy number variation (CNV) calling software offers the advantages of providing both genetic (copy-number) and epigenetic (methylation) state information from a single genomic library. This method is advantageous when looking at large-scale chromosomal rearrangements such as the loss of the short arm of chromosome 3 (3p) in renal cell carcinoma and the codeletion of the short arm of chromosome 1 and the long arm of chromosome 19 (1p/19q) commonly seen in histologically defined oligodendrogliomas. Herein, we present MethylMasteR: a software framework that facilitates the standardization and customization of methylation-based CNV calling algorithms in a single R package deployed using the Docker software framework. This framework allows for the easy comparison of the performance and the large-scale CNV event identification capability of four common methylation-based CNV callers. Additionally, we incorporated our custom routine, which was among the best performing routines. We employed the Affymetrix 6.0 SNP Chip results as a gold standard against which to compare large-scale event recall. As there are disparities within the software calling algorithms themselves, no single software is likely to perform best for all samples and all combinations of parameters. The employment of a standardized software framework via creating a Docker image and its subsequent deployment as a Docker container allows researchers to efficiently compare algorithms and lends itself to the development of modified workflows such as the custom workflow we have developed. Researchers can now use the MethylMasteR software for their methylation-based CNV calling needs and follow our software deployment framework. We will continue to refine our methodology in the future with a specific focus on identifying large-scale chromosomal rearrangements in cancer methylation data.

CNV detection and their association with growth, efficiency and carcass traits in Santa Inês sheep

Copy number variations (CNV) are an important source of genetic variation. CNV has been increasingly studied and frequently associated with diseases and productive traits in livestock animals. However, CNV-based genome-wide association studies (GWAS) in Santa Inês sheep, one of the principal sheep breeds in Brazil, have not yet been reported. Thus, the aim of this study was to investigate the association between CNV and growth, efficiency and carcass traits in sheep. The Illumina OvineSNP50 BeadChip array was used to detect CNV in 491 Santa Inês individuals. Then, CNV-based GWAS was performed with a linear mixed model approach considering a genomic relationship matrix, for ten traits: (1) growth: body weight at three (W3) and six (W6) months of age; (2) efficiency: residual feed intake (RFI) and feed efficiency (FE) and (3) carcass: external carcass length (ECL), leg length (LL), carcass yield (CY), commercial cuts weight (CCW), loin eye area (LEA) and subcutaneous fat thickness (SFT). We identified 1,167 autosomal CNV in 438 sheep, with 294 non-redundant CNV, ranging from 21.8 to 861.9 kb, merged into 216 distinct copy number variation regions (CNVRs). One significant CNV segment (p_FDR -value<0.05) in OAR3 was associated with CY, while another significant CNV in OAR6 was associated with RFI. Additionally, another 5 CNV segments were considered relevant for investigation in the future studies. The significant segments overlapped 4 QTLs and spanned 8 genes, including the SPAST, TGFA and ADGRL3 genes, involved in cell differentiation and energy metabolism. Therefore, the results of the present study increase knowledge about CNV in sheep, their possible impacts on productive traits, and provide information for future investigations, being especially useful for those interested in structural variations in the sheep genome.

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.

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

Background

Copy 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.

Results

We 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.

Conclusions

Overall, 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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07676-1.