Genome-wide Mapping of Copy Number Variations Using SNP Arrays

Advancements in copy number variation screening in herbivorous livestock genomes and their association with phenotypic traits

Copy number variations (CNVs) have garnered increasing attention within the realm of genetics due to their prevalence in human, animal, and plant genomes. These structural genetic variations have demonstrated associations with a broad spectrum of phenotypic diversity, economic traits, environmental adaptations, epidemics, and other essential aspects of both plants and animals. Furthermore, CNVs exhibit extensive sequence variability and encompass a wide array of genomes. The advancement and maturity of microarray and sequencing technologies have catalyzed a surge in research endeavors pertaining to CNVs. This is particularly prominent in the context of livestock breeding, where molecular markers have gained prominence as a valuable tool in comparison to traditional breeding methods. In light of these developments, a contemporary and comprehensive review of existing studies on CNVs becomes imperative. This review serves the purpose of providing a brief elucidation of the fundamental concepts underlying CNVs, their mutational mechanisms, and the diverse array of detection methods employed to identify these structural variations within genomes. Furthermore, it seeks to systematically analyze the recent advancements and findings within the field of CNV research, specifically within the genomes of herbivorous livestock species, including cattle, sheep, horses, and donkeys. The review also highlighted the role of CNVs in shaping various phenotypic traits including growth traits, reproductive traits, pigmentation and disease resistance etc., in herbivorous livestock. The main goal of this review is to furnish readers with an up-to-date compilation of knowledge regarding CNVs in herbivorous livestock genomes. By integrating the latest research findings and insights, it is anticipated that this review will not only offer pertinent information but also stimulate future investigations into the realm of CNVs in livestock. In doing so, it endeavors to contribute to the enhancement of breeding strategies, genomic selection, and the overall improvement of herbivorous livestock production and resistance to diseases.

Genomic copy number variation correlates with survival outcomes in WHO grade IV glioma

Allele-specific copy number analysis of tumors (ASCAT) assesses copy number variations (CNV) while accounting for aberrant cell fraction and tumor ploidy. We evaluated if ASCAT-assessed CNV are associated with survival outcomes in 56 patients with WHO grade IV gliomas. Tumor data analyzed by Affymetrix OncoScan FFPE Assay yielded the log ratio (R) and B-allele frequency (BAF). Input into ASCAT quantified CNV using the segmentation function to measure copy number inflection points throughout the genome. Quantified CNV was reported as log R and BAF segment counts. Results were confirmed on The Cancer Genome Atlas (TCGA) glioblastoma dataset. 25 (44.6%) patients had MGMT hyper-methylated tumors, 6 (10.7%) were IDH1 mutated. Median follow-up was 36.4 months. Higher log R segment counts were associate with longer progression-free survival (PFS) [hazard ratio (HR) 0.32, p < 0.001], and overall survival (OS) [HR 0.45, p = 0.01], and was an independent predictor of PFS and OS on multivariable analysis. Higher BAF segment counts were linked to longer PFS (HR 0.49, p = 0.022) and OS (HR 0.49, p = 0.052). In the TCGA confirmation cohort, longer 12-month OS was seen in patients with higher BAF segment counts (62.3% vs. 51.9%, p = 0.0129) and higher log R (63.6% vs. 55.2%, p = 0.0696). Genomic CNV may be a novel prognostic biomarker for WHO grade IV glioma patient outcomes.

Autism spectrum disorders: Integration of the genome, transcriptome and the environment

Autism spectrum disorders denote a series of lifelong neurodevelopmental conditions characterized by an impaired social communication profile and often repetitive, stereotyped behavior. Recent years have seen the complex genetic architecture of the disease being progressively unraveled with advancements in gene finding technology and next generation sequencing methods. However, a complete elucidation of the molecular mechanisms behind autism is necessary for potential diagnostic and therapeutic applications. A multidisciplinary approach should be adopted where the focus is not only on the 'genetics' of autism but also on the combinational roles of epigenetics, transcriptomics, immune system disruption and environmental factors that could all influence the etiopathogenesis of the disease. ASD is a clinically heterogeneous disorder with great genetic complexity; only through an integrated multidimensional effort can modern autism research progress further.

Deciphering global signal features of high-throughput array data from cancers

Normalization of array data relies on the assumption that most genes are not altered, which means that the signals for different samples should be scaled to have similar median or average values. However, accumulating evidence suggests that gene expression could be widely up-regulated in cancers. Our previous results and subsequent findings have shown that violation of the assumption led to erroneous interpretation of microarray data. To decipher the global signal features of microarray data from cancer samples, we empirically evaluated a large collection of gene and miRNA expression profiles and copy-number variation arrays. Our results showed that, at the transcriptomic level, genes and miRNAs are widely over-expressed in a large proportion of cancers. In contrast, at the genomic level, global raw signal intensities for methylation and copy number variation show negligible differences between cancer and normal samples. These results force us to re-evaluate the proper use of normalization procedures under different experimental conditions and for different array platforms.

Chromosome microarrays in human reproduction

BACKGROUND

Chromosome microarray (CMA) testing allows automatic and easy identification of large chromosomal abnormalities detectable by conventional cytogenetics as well as the detection of submicroscopic chromosomal imbalances.

METHODS

A PubMed search was performed in order to review the current use of CMA testing in the field of human reproduction. Articles discussing the use of CMA in the preimplantation setting, ongoing pregnancies, miscarriages and patients with reproductive disorders were considered.

RESULTS

A high rate of concordance between conventional methods of detecting chromosomal abnormalities [e.g. fluorescence in situ hybridization (FISH), karyotyping] and CMA was reported in the prenatal setting with CMA providing more comprehensive and detailed results as it investigates the whole genome at higher resolution. In preimplantation genetic screening, CMA is replacing FISH and the selection of embryos based on CMA has already resulted in live births. For ongoing pregnancies and miscarriages, CMA eliminates tissue culture failures and artifacts and allows a quick turnaround time. The detection of submicroscopic imbalances [or copy number variants (CNVs)] is beneficial when the imbalance has a clear clinical consequence but is challenging for previously undescribed imbalances, particularly for ongoing pregnancies. Recurrent CNVs have been documented in patients with reproductive disorders; however, the application of CMA in this field is still limited.

CONCLUSIONS

CMA enhances reproductive medicine as it facilitates better understanding of the genetic aspects of human development and reproduction and more informed patient management. Further clinical validation of CMA in the prenatal setting, creation of practice guidelines and catalogs of newly discovered submicroscopic imbalances with clinical outcomes are areas that will require attention in the future.