Global variation in copy number in the human genome

Adap-BDCM: Adaptive Bilinear Dynamic Cascade Model for Classification Tasks on CNV Datasets

Copy number variation (CNV) is an essential genetic driving factor of cancer formation and progression, making intelligent classification based on CNV feasible. However, there are a few challenges in the current machine learning and deep learning methods, such as the design of base classifier combination schemes in ensemble methods and the selection of layers of neural networks, which often result in low accuracy. Therefore, an adaptive bilinear dynamic cascade model (Adap-BDCM) is developed to further enhance the accuracy and applicability of these methods for intelligent classification on CNV datasets. In this model, a feature selection module is introduced to mitigate the interference of redundant information, and a bilinear model based on the gated attention mechanism is proposed to extract more beneficial deep fusion features. Furthermore, an adaptive base classifier selection scheme is designed to overcome the difficulty of manually designing base classifier combinations and enhance the applicability of the model. Lastly, a novel feature fusion scheme with an attribute recall submodule is constructed, effectively avoiding getting stuck in local solutions and missing some valuable information. Numerous experiments have demonstrated that our Adap-BDCM model exhibits optimal performance in cancer classification, stage prediction, and recurrence on CNV datasets. This study can assist physicians in making diagnoses faster and better.

A comprehensive review of livestock development: insights into domestication, phylogenetics, diversity, and genomic advances

Livestock plays an essential role in sustaining human livelihoods, offering a diverse range of species integral to food security, economic stability, and cultural traditions. The domestication of livestock, which began over 10,000 years ago, has driven significant genetic changes in species such as cattle, buffaloes, sheep, goats, and pigs. Recent advancements in genomic technologies, including next-generation sequencing (NGS), genome-wide association studies (GWAS), and genomic selection, have dramatically enhanced our understanding of these genetic developments. This review brings together key research on the domestication process, phylogenetics, genetic diversity, and selection signatures within major livestock species. It emphasizes the importance of admixture studies and evolutionary forces like natural selection, genetic drift, and gene flow in shaping livestock populations. Additionally, the integration of machine learning with genomic data offers new perspectives on the functional roles of genes in adaptation and evolution. By exploring these genomic advancements, this review provides insights into genetic variation and evolutionary processes that could inform future approaches to improving livestock management and adaptation to environmental challenges, including climate change.

Genotyping sequence-resolved copy-number variations using pangenomes reveals paralog-specific global diversity and expression divergence of duplicated genes

Copy-number variable (CNV) genes are important in evolution and disease, yet sequence variation in CNV genes is a blindspot for large-scale studies. We present a method, ctyper, that leverages pangenomes to produce copy-number maps with allele-specific sequences containing locally phased variants of CNV genes from NGS reads. We extensively characterized accuracy and efficiency on a database of 3,351 CNV genes including HLA , SMN , and CYP2D6 as well as 212 non-CNV medically-relevant challenging genes. The genotypes capture 96.5% of underlying variants in new genomes, requiring 0.9 seconds per gene. Expression analysis of ctyper genotypes explains more variance than known eQTL variants. Comparing allele-specific expression quantified divergent expression on 7.94% of paralogs and tissue-specific biases on 4.7% of paralogs. We found reduced expression of SMN-1 converted from SMN-2, which potentially affects diagnosis of spinal muscular atrophy, and increased expression of a duplicative translocation of AMY2B . Overall, ctyper enables biobank-scale genotyping of CNV and challenging genes.

Copy-number variants differ in frequency across genetic ancestry groups

Copy-number variants (CNVs) have been implicated in a variety of neuropsychiatric and cognitive phenotypes. We found that deleterious CNVs are less prevalent in non-European ancestry groups than they are in European ancestry groups of both the UK Biobank (UKBB) and a US replication cohort (SPARK). We also identified specific recurrent CNVs that consistently differ in frequency across ancestry groups in both the UKBB and SPARK. These ancestry-related differences in CNV prevalence present in both an unselected community population and a family cohort enriched with individuals diagnosed with autism spectrum disorder (ASD) strongly suggest that genetic ancestry should be considered when probing associations between CNVs and health outcomes.

Genome-wide association testing beyond SNPs

Decades of genetic association testing in human cohorts have provided important insights into the genetic architecture and biological underpinnings of complex traits and diseases. However, for certain traits, genome-wide association studies (GWAS) for common SNPs are approaching signal saturation, which underscores the need to explore other types of genetic variation to understand the genetic basis of traits and diseases. Copy number variation (CNV) is an important source of heritability that is well known to functionally affect human traits. Recent technological and computational advances enable the large-scale, genome-wide evaluation of CNVs, with implications for downstream applications such as polygenic risk scoring and drug target identification. Here, we review the current state of CNV-GWAS, discuss current limitations in resource infrastructure that need to be overcome to enable the wider uptake of CNV-GWAS results, highlight emerging opportunities and suggest guidelines and standards for future GWAS for genetic variation beyond SNPs at scale.

Loss of genetic variation and ancestral sex determination system in North American northern pike characterized by whole-genome resequencing

The northern pike Esox lucius is a freshwater fish with low genetic diversity but ecological success throughout the Northern Hemisphere. Here, we generate an annotated chromosome-level genome assembly of 941 Mbp in length with 25 chromosome-length scaffolds. We then genotype 47 northern pike from Alaska through New Jersey at a genome-wide scale and characterize a striking decrease in genetic diversity along the sampling range. Individuals west of the North American Continental Divide have substantially higher diversity than those to the east (e.g. Interior Alaska and St. Lawrence River have on average 181 and 64K heterozygous SNPs per individual, or a heterozygous SNP every 5.2 and 14.6 kbp, respectively). Individuals clustered within each population with strong support, with numerous private alleles observed within each population. Evidence for recent population expansion was observed for a Manitoba hatchery and the St. Lawrence population (Tajima's D = -1.07 and -1.30, respectively). Several chromosomes have large regions with elevated diversity, including LG24, which holds amhby, the ancestral sex determining gene. As expected amhby was largely male-specific in Alaska and the Yukon and absent southeast to these populations, but we document some amhby(-) males in Alaska and amhby(+) males in the Columbia River, providing evidence for a patchwork of presence of this system in the western region. These results support the theory that northern pike recolonized North America from refugia in Alaska and expanded following deglaciation from west to east, with probable founder effects resulting in loss of both neutral and functional diversity (e.g. amhby).

Genome-wide association study reveals 2 copy number variations associated with the variation of plumage color in the white duck hybrid population

Plumage color is an intuitive external poultry characteristic with rich manifestations and complex genetic mechanisms. In our previous study, we observed that there were more dark variations in plumage color in the F2 population derived from the hybridization of 2 white duck varieties. Therefore, based on the statistics of plumage color of 308 F2 populations, we further used the resequencing data of these individuals to detect copy number variations (CNVs) in the whole genome and conducted genome-wide association studies (GWAS) to determine the genetic basis related to plumage color traits. The CNV detection revealed 9,337 CNVs, with an average length of 15,950 bp and a total length of 142.02 MB, accounting for approximately 12.91% of the reference genome. The CNV distribution on the chromosomes was relatively uniform, and the number of CNVs on each chromosome positively correlated with the length of the chromosome. In the pure black plumage group, 2,101 CNVs were only identified, and 1,714 were specifically identified in the pure white plumage group. Ten CNVs were randomly selected for validation using quantitative real-time PCR, and 9 CNVs had the same CNV types as predicted, with an accuracy of 90%. Based on GWAS, we identified 2 CNVs potentially associated with plumage color variations, with the associated CNV regions covering 9 genes. Enrichment analysis of these 9 candidate genes showed significant enrichment of 3 pathways (ribosome biogenesis in eukaryotes, RNA transport, and protein export) and 17 gene ontology terms. Among these, VWA5A can downregulate MITF by binding to the regulatory factors SOX10. The occurrence of CNV may indirectly contribute to duck plumage color variation by affecting the regulatory factors of the switch gene MITF in the melanogenesis pathway. These findings have improved the understanding of the genetic basis of duck plumage color variation and have been beneficial for developing and using plumage color traits in subsequent poultry breeding.

Copy number amplification-induced overexpression of lncRNA LOC101927668 facilitates colorectal cancer progression by recruiting hnRNPD to disrupt RBM47/p53/p21 signaling

BACKGROUND

Somatic copy number alterations (SCNAs) are pivotal in cancer progression and patient prognosis. Dysregulated long non-coding RNAs (lncRNAs), modulated by SCNAs, significantly impact tumorigenesis, including colorectal cancer (CRC). Nonetheless, the functional significance of lncRNAs induced by SCNAs in CRC remains largely unexplored.

METHODS

The dysregulated lncRNA LOC101927668, induced by copy number amplification, was identified through comprehensive bioinformatic analyses utilizing multidimensional data. Subsequent in situ hybridization was employed to ascertain the subcellular localization of LOC101927668, and gain- and loss-of-function experiments were conducted to elucidate its role in CRC progression. The downstream targets and signaling pathway influenced by LOC101927668 were identified and validated through a comprehensive approach, encompassing RNA sequencing, RT-qPCR, Western blot analysis, dual-luciferase reporter assay, evaluation of mRNA and protein degradation, and rescue experiments. Analysis of AU-rich elements (AREs) within the mRNA 3' untranslated region (UTR) of the downstream target, along with exploration of putative ARE-binding proteins, was conducted. RNA pull-down, mass spectrometry, RNA immunoprecipitation, and dual-luciferase reporter assays were employed to elucidate potential interacting proteins of LOC101927668 and further delineate the regulatory mechanism between LOC101927668 and its downstream target. Moreover, subcutaneous xenograft and orthotopic liver xenograft tumor models were utilized to evaluate the in vivo impact of LOC101927668 on CRC cells and investigate its correlation with downstream targets.

RESULTS

Significantly overexpressed LOC101927668, driven by chr7p22.3-p14.3 amplification, was markedly correlated with unfavorable clinical outcomes in our CRC patient cohort, as well as in TCGA and GEO datasets. Moreover, we demonstrated that enforced expression of LOC101927668 significantly enhanced cell proliferation, migration, and invasion, while its depletion impeded these processes in a p53-dependent manner. Mechanistically, nucleus-localized LOC101927668 recruited hnRNPD and translocated to the cytoplasm, accelerating the destabilization of RBM47 mRNA, a transcription factor of p53. As a nucleocytoplasmic shuttling protein, hnRNPD mediated RBM47 destabilization by binding to the ARE motif within RBM47 3'UTR, thereby suppressing the p53 signaling pathway and facilitating CRC progression.

CONCLUSIONS

The overexpression of LOC101927668, driven by SCNAs, facilitates CRC proliferation and metastasis by recruiting hnRNPD, thus perturbing the RBM47/p53/p21 signaling pathway. These findings underscore the pivotal roles of LOC101927668 and highlight its therapeutic potential in anti-CRC interventions.

Fc gamma receptors: Their evolution, genomic architecture, genetic variation, and impact on human disease

Fc gamma receptors (FcγRs) are a family of receptors that bind IgG antibodies and interface at the junction of humoral and innate immunity. Precise regulation of receptor expression provides the necessary balance to achieve healthy immune homeostasis by establishing an appropriate immune threshold to limit autoimmunity but respond effectively to infection. The underlying genetics of the FCGR gene family are central to achieving this immune threshold by regulating affinity for IgG, signaling efficacy, and receptor expression. The FCGR gene locus was duplicated during evolution, retaining very high homology and resulting in a genomic region that is technically difficult to study. Here, we review the recent evolution of the gene family in mammals, its complexity and variation through copy number variation and single-nucleotide polymorphism, and impact of these on disease incidence, resolution, and therapeutic antibody efficacy. We also discuss the progress and limitations of current approaches to study the region and emphasize how new genomics technologies will likely resolve much of the current confusion in the field. This will lead to definitive conclusions on the impact of genetic variation within the FCGR gene locus on immune function and disease.

Gene expansions contributing to human brain evolution

Genomic drivers of human-specific neurological traits remain largely undiscovered. Duplicated genes expanded uniquely in the human lineage likely contributed to brain evolution, including the increased complexity of synaptic connections between neurons and the dramatic expansion of the neocortex. Discovering duplicate genes is challenging because the similarity of paralogs makes them prone to sequence-assembly errors. To mitigate this issue, we analyzed a complete telomere-to-telomere human genome sequence (T2T-CHM13) and identified 213 duplicated gene families likely containing human-specific paralogs (>98% identity). Positing that genes important in universal human brain features should exist with at least one copy in all modern humans and exhibit expression in the brain, we narrowed in on 362 paralogs with at least one copy across thousands of ancestrally diverse genomes and present in human brain transcriptomes. Of these, 38 paralogs co-express in gene modules enriched for autism-associated genes and potentially contribute to human language and cognition. We narrowed in on 13 duplicate gene families with human-specific paralogs that are fixed among modern humans and show convincing brain expression patterns. Using long-read DNA sequencing revealed hidden variation across 200 modern humans of diverse ancestries, uncovering signatures of selection not previously identified, including possible balancing selection of CD8B. To understand the roles of duplicated genes in brain development, we generated zebrafish CRISPR "knockout" models of nine orthologs and transiently introduced mRNA-encoding paralogs, effectively "humanizing" the larvae. Morphometric, behavioral, and single-cell RNA-seq screening highlighted, for the first time, a possible role for GPR89B in dosage-mediated brain expansion and FRMPD2B function in altered synaptic signaling, both hallmark features of the human brain. Our holistic approach provides important insights into human brain evolution as well as a resource to the community for studying additional gene expansion drivers of human brain evolution.

Genome sequencing in the prenatal diagnosis of structural malformations in the fetus

Prenatal genetic diagnosis has undergone two pivotal paradigm shifts, initially with the introduction of chromosomal microarray and subsequently with the advent of next-generation sequencing technologies (NGS). NGS technology has given rise to a multitude of applications, with gene panels, exome sequencing (ES), and genome sequencing (GS) emerging as highly promising tests for prenatal genetic investigations. These advanced approaches have demonstrated superior diagnostic rates when compared to conventional testing methods, showcasing the evolution and enhancement of prenatal genetic screening and diagnostic capabilities. With these ground-breaking innovations, NGS technologies have the potential to replace current standard practice in prenatal diagnosis. With the increasing use of prenatal sequencing, the need for better education and guidance on their applications grows. This chapter aims to illustrate the detection scope and feasibility of various NGS-based methods that are currently used in prenatal diagnosis.

Genome-Wide Analysis Reveals Copy Number Variant Gene TGFBR3 Regulates Pig Back Fat Deposition

BFT is closely related to meat quality and lean meat percentage in pigs. The BFT traits of European LW pigs significantly differ from those of Chinese indigenous fatty MZ pigs. CNV is a prevalent genetic variation that plays an important role in economically important traits in pigs. However, the potential contribution of CNV to BFT in LW and MZ pigs remains unclear. In this study, whole-genome CNV detection was performed using next-generation sequencing data from LW and MZ pigs, and transcriptome data from back fat tissue of 180-day-old LW and MZ pigs were integrated for expression quantitative trait loci (eQTL) analysis. We identified a copy number variation in the TGFBR3 gene associated with BFT, showing a dose effect between the genome and transcriptome levels of the TGFBR3 gene. In porcine preadipocytes, TGFBR3 expression continuously increased during differentiation. Knockdown of TGFBR3 using specific siRNA inhibited preadipocyte differentiation and proliferation. Our study provides insights into the genetic regulation of pork quality and offers a theoretical basis for improving carcass quality by modulating BFT in pigs.

From genes to therapy: A comprehensive exploration of congenital heart disease through the lens of genetics and emerging technologies

Congenital heart disease (CHD) affects approximately 1 % of live births worldwide, making it the most common congenital anomaly in newborns. Recent advancements in genetics and genomics have significantly deepened our understanding of the genetics of CHDs. While the majority of CHD etiology remains unclear, evidence consistently indicates that genetics play a significant role in its development. CHD etiology holds promise for enhancing diagnosis and developing novel therapies to improve patient outcomes. In this review, we explore the contributions of both monogenic and polygenic factors of CHDs and highlight the transformative impact of emerging technologies on these fields. We also summarized the state-of-the-art techniques, including targeted next-generation sequencing (NGS), whole genome and whole exome sequencing (WGS, WES), single-cell RNA sequencing (scRNA-seq), human induced pluripotent stem cells (hiPSCs) and others, that have revolutionized our understanding of cardiovascular disease genetics both from diagnosis perspective and from disease mechanism perspective in children and young adults. These molecular diagnostic techniques have identified new genes and chromosomal regions involved in syndromic and non-syndromic CHD, enabling a more defined explanation of the underlying pathogenetic mechanisms. As our knowledge and technologies continue to evolve, they promise to enhance clinical outcomes and reduce the CHD burden worldwide.

Genome-wide association analyses reveal copy number variant regions associated with reproduction and disease traits in Canadian Holstein cattle

This study aimed to evaluate the impact of copy number variants (CNV) on 13 reproduction and 12 disease traits in Holstein cattle. Intensity signal files containing log R ratio and B allele frequency information from 13,730 Holstein animals genotyped with a 95K SNP panel, and 8,467 Holstein animals genotyped with a 50K SNP panel were used to identify the CNVs. Subsequently, the identified CNVs were validated using whole-genome sequence data from 126 animals, resulting in 870 high-confidence copy number variant regions (CNVR) on 12,131 animals. Out of these, 54 CNVR had frequencies higher than or equal to 1% in the population and were used in the genome-wide association analysis (one CNVR at a time, including the G matrix). Results revealed that 4 CNVR were significantly associated with at least one of the traits analyzed in this study. Specifically, 2 CNVR were associated with 3 reproduction traits (i.e., calf survival, first service to conception, and nonreturn rate), and 2 CNVR were associated with 2 disease traits (i.e., metritis and retained placenta). These CNVR harbored genes implicated in immune response, cellular signaling, and neuronal development, supporting their potential involvement in these traits. Further investigations to unravel the mechanistic and functional implications of these CNVR on the mentioned traits are warranted.

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.

CNVDeep: deep association of copy number variants with neurocognitive disorders

BACKGROUND

Copy number variants (CNVs) have become increasingly instrumental in understanding the etiology of all diseases and phenotypes, including Neurocognitive Disorders (NDs). Among the well-established regions associated with ND are small parts of chromosome 16 deletions (16p11.2) and chromosome 15 duplications (15q3). Various methods have been developed to identify associations between CNVs and diseases of interest. The majority of methods are based on statistical inference techniques. However, due to the multi-dimensional nature of the features of the CNVs, these methods are still immature. The other aspect is that regions discovered by different methods are large, while the causative regions may be much smaller.

RESULTS

In this study, we propose a regularized deep learning model to select causal regions for the target disease. With the help of the proximal [20] gradient descent algorithm, the model utilizes the group LASSO concept and embraces a deep learning model in a sparsity framework. We perform the CNV analysis for 74,811 individuals with three types of brain disorders, autism spectrum disorder (ASD), schizophrenia (SCZ), and developmental delay (DD), and also perform cumulative analysis to discover the regions that are common among the NDs. The brain expression of genes associated with diseases has increased by an average of 20 percent, and genes with homologs in mice that cause nervous system phenotypes have increased by 18 percent (on average). The DECIPHER data source also seeks other phenotypes connected to the detected regions alongside gene ontology analysis. The target diseases are correlated with some unexplored regions, such as deletions on 1q21.1 and 1q21.2 (for ASD), deletions on 20q12 (for SCZ), and duplications on 8p23.3 (for DD). Furthermore, our method is compared with other machine learning algorithms.

CONCLUSIONS

Our model effectively identifies regions associated with phenotypic traits using regularized deep learning. Rather than attempting to analyze the whole genome, CNVDeep allows us to focus only on the causative regions of disease.

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.

Strategic targeting of Cas9 nickase induces large segmental duplications

Gene/segmental duplications play crucial roles in genome evolution and variation. Here, we introduce paired nicking-induced amplification (PNAmp) for their experimental induction. PNAmp strategically places two Cas9 nickases upstream and downstream of a replication origin on opposite strands. This configuration directs the sister replication forks initiated from the origin to break at the nicks, generating a pair of one-ended double-strand breaks. If homologous sequences flank the two break sites, then end resection converts them to single-stranded DNAs that readily anneal to drive duplication of the region bounded by the homologous sequences. PNAmp induces duplication of segments as large as ∼1 Mb with efficiencies exceeding 10% in the budding yeast Saccharomyces cerevisiae. Furthermore, appropriate splint DNAs allow PNAmp to duplicate/multiplicate even segments not bounded by homologous sequences. We also provide evidence for PNAmp in mammalian cells. Therefore, PNAmp provides a prototype method to induce structural variations by manipulating replication fork progression.

Genetic diversity and signatures of selection in Icelandic horses and Exmoor ponies

BACKGROUND

The Icelandic horse and Exmoor pony are ancient, native breeds, adapted to harsh environmental conditions and they have both undergone severe historic bottlenecks. However, in modern days, the selection pressures on these breeds differ substantially. The aim of this study was to assess genetic diversity in both breeds through expected (HE) and observed heterozygosity (HO) and effective population size (Ne). Furthermore, we aimed to identify runs of homozygosity (ROH) to estimate and compare genomic inbreeding and signatures of selection in the breeds.

RESULTS

HO was estimated at 0.34 and 0.33 in the Icelandic horse and Exmoor pony, respectively, aligning closely with HE of 0.34 for both breeds. Based on genomic data, the Ne for the last generation was calculated to be 125 individuals for Icelandic horses and 42 for Exmoor ponies. Genomic inbreeding coefficient (FROH) ranged from 0.08 to 0.20 for the Icelandic horse and 0.12 to 0.27 for the Exmoor pony, with the majority of inbreeding attributed to short ROHs in both breeds. Several ROH islands associated with performance were identified in the Icelandic horse, featuring target genes such as DMRT3, DOCK8, EDNRB, SLAIN1, and NEURL1. Shared ROH islands between both breeds were linked to metabolic processes (FOXO1), body size, and the immune system (CYRIB), while private ROH islands in Exmoor ponies were associated with coat colours (ASIP, TBX3, OCA2), immune system (LYG1, LYG2), and fertility (TEX14, SPO11, ADAM20).

CONCLUSIONS

Evaluations of genetic diversity and inbreeding reveal insights into the evolutionary trajectories of both breeds, highlighting the consequences of population bottlenecks. While the genetic diversity in the Icelandic horse is acceptable, a critically low genetic diversity was estimated for the Exmoor pony, which requires further validation. Identified signatures of selection highlight the differences in the use of the two breeds as well as their adaptive trait similarities. The results provide insight into genomic regions under selection pressure in a gaited performance horse breed and various adaptive traits in small-sized native horse breeds. This understanding contributes to preserving genetic diversity and population health in these equine populations.

A Comparison of Tools That Identify Tumor Cells by Inferring Copy Number Variations from Single-Cell Experiments in Pancreatic Ductal Adenocarcinoma

Single-cell RNA sequencing (scRNA-seq) technique has enabled detailed analysis of gene expression at the single cell level, enhancing the understanding of subtle mechanisms that underly pathologies and drug resistance. To derive such biological meaning from sequencing data in oncology, some critical processing must be performed, including identification of the tumor cells by markers and algorithms that infer copy number variations (CNVs). We compared the performance of sciCNV, InferCNV, CopyKAT and SCEVAN tools that identify tumor cells by inferring CNVs from scRNA-seq data. Sequencing data from Pancreatic Ductal Adenocarcinoma (PDAC) patients, adjacent and healthy tissues were analyzed, and the predicted tumor cells were compared to those identified by well-assessed PDAC markers. Results from InferCNV, CopyKAT and SCEVAN overlapped by less than 30% with InferCNV showing the highest sensitivity (0.72) and SCEVAN the highest specificity (0.75). We show that the predictions are highly dependent on the sample and the software used, and that they return so many false positives hence are of little use in verifying or filtering predictions made via tumor biomarkers. We highlight how critical this processing can be, warn against the blind use of these software and point out the great need for more reliable algorithms.

Diffuse large B-cell lymphoma with DNA copy number changes in a Japanese black calf

A 2-month-old Japanese Black calf exhibited mandibular and superficial cervical lymph node swelling. Fine needle aspiration cytology of the superficial cervical lymph node revealed large lymphoblast-like cells with mitoses. Hematological examination revealed remarkable lymphocytosis with atypical lymphocytes. Increased activities of serum total lactate dehydrogenase and thymidine kinase were detected. At necropsy, generalized swelling of lymph nodes was observed. Histopathological analysis revealed diffuse proliferation of medium-sized round centroblastic neoplastic cells that were positive for CD20, CD79α, PAX5, and BLA-36, and negative for CD3, CD5, CD10, and CD34. The calf was diagnosed with centroblastic diffuse large B-cell lymphoma (DLBCL) based on these findings. Analysis of DNA copy number variation revealed an increased copy number for the GIMAP family relative to that in healthy cattle. Moreover, decreases in copy numbers of GBP-1, MIR3141, OR5P1E, and PTPRG relative to those in healthy cattle were also observed. Because DNA copy number variation represent a major contribution to the somatic mutation landscapes in human tumors, these findings suggest that DNA copy number changes might have contributed to the onset of DLBCL in the present case.

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.

Genome-wide detection of multiple variants associated with teat number in French Yorkshire pigs

BACKGROUND

Teat number is a vital reproductive trait in sows, crucial for providing immunity and nutrition to piglets during lactation. However, "missing heritability" in Single Nucleotide Polymorphism (SNP)-based Genome-Wide Association Studies (GWAS) has led to an increasing focus on structural variations in the genetic analysis of complex biological traits.

RESULTS

In this study, we generated a comprehensive CNV map in a population of French Yorkshire pigs (n = 644) and identified 429 CNVRs. Notably, 44% (189 CNVRs) of these were detected for the first time. Subsequently, we conducted GWAS for teat number in the French Yorkshire pig population using both 80K chip and its imputed data, as well as a GWAS analysis based on CNV regions (CNVR). Interestingly, 80K chip GWAS identified two SNPs located on Sus scrofa chromosome 5 (SSC5) that were simultaneously associated with Total Teat Number (TTN), Left Teat Number (LTN), and Right Teat Number (RTN). The leading SNP (WU_10.2_5_76130558) explained 3.33%, 2.69%, and 2.67% of the phenotypic variance for TTN, LTN, and RTN, respectively. Moreover, through imputed GWAS, we successfully identified 30 genetic variants associated with TTN located within the 73.22 -73.30 Mb region on SSC5. The two SNPs identified in the 80K chip GWAS were also located in this region. In addition, CNVR-based GWAS revealed three significant CNVRs associated with TTN. Finally, through gene annotation, we pinpointed two candidate genes, TRIM66 and PRICKLE1, which are related to diverse processes such as breast cancer and abnormal vertebral development.

CONCLUSIONS

Our research provides an in-depth analysis of the complex genetic structure underlying teat number, contributing to the genetic enhancement of sows with improved reproductive performance and, ultimately, bolstering the economic benefits of swine production enterprises.

Analysis of genomic copy number variations through whole-genome scan in Yunling cattle

Yunling cattle is a new breed of beef cattle bred in Yunnan Province, China, which has the advantages of fast growth, excellent meat quality, improved tolerance ability, and important landscape value. Copy number variation (CNV) is a significant source of gene structural variation and plays a crucial role in evolution and phenotypic diversity. Based on the latest reference genome ARS-UCD2.0, this study analyzed the genome-wide distribution of CNVs in Yunling cattle using short-read whole-genome sequencing data (n = 129) and single-molecule long-read sequencing data (n = 1), and a total of 16,507 CNVs were detected. After merging CNVs with overlapping genomic positions, 3,728 CNV regions (CNVRs) were obtained, accounting for 0.61% of the reference genome. The functional analysis indicated significant enrichment of CNVRs in 96 GO terms and 57 KEGG pathways, primarily related to cell adhesion, signal transduction, neuromodulation, and nutritional metabolism. Additionally, 111 CNVRs overlapped with 76 quantitative trait loci (QTLs), including Subcutaneous fat thickness QTL, Longissimus muscle area QTL, and Marbling score QTL. Several CNVR-overlapping genes, including BZW1, AOX1, and LOC100138449, overlap with regions associated with meat color and quality QTLs. Furthermore, Vst analysis showed that PSMB4, ERICH1, SMC2, and PPP4R3A were highly divergent between Yunling and Brahman cattle. In summary, we have constructed the genomic CNV map of Yunling cattle for the first time using whole-genome resequencing. This provides valuable genetic variation resources for the study of the Yunling cattle genome and contributes to the study of economic traits in Yunling cattle.

A comprehensive review of deep learning-based variant calling methods

Genome sequencing data have become increasingly important in the field of personalized medicine and diagnosis. However, accurately detecting genomic variations remains a challenging task. Traditional variation detection methods rely on manual inspection or predefined rules, which can be time-consuming and prone to errors. Consequently, deep learning-based approaches for variation detection have gained attention due to their ability to automatically learn genomic features that distinguish between variants. In our review, we discuss the recent advancements in deep learning-based algorithms for detecting small variations and structural variations in genomic data, as well as their advantages and limitations.

An assessment of the genomic structural variation landscape in Sub-Saharan African populations

Structural variants are responsible for a large part of genomic variation between individuals and play a role in both common and rare diseases. Databases cataloguing structural variants notably do not represent the full spectrum of global diversity, particularly missing information from most African populations. To address this representation gap, we analysed 1,091 high-coverage African genomes, 545 of which are public data sets, and 546 which have been analysed for structural variants for the first time. Variants were called using five different tools and datasets merged and jointly called using SURVIVOR. We identified 67,795 structural variants throughout the genome, with 10,421 genes having at least one variant. Using a conservative overlap in merged data, 6,414 of the structural variants (9.5%) are novel compared to the Database of Genomic Variants. This study contributes to knowledge of the landscape of structural variant diversity in Africa and presents a reliable dataset for potential applications in population genetics and health-related research.

Comparison of the diagnostic significance of cerebrospinal fluid metagenomic next-generation sequencing copy number variation analysis and cytology in leptomeningeal malignancy

BACKGROUND

Diagnosis and monitoring of leptomeningeal malignancy remain challenging, and are usually based on neurological, radiological, cerebrospinal fluid (CSF) and pathological findings. This study aimed to investigate the diagnostic performance of CSF metagenomic next-generation sequencing (mNGS) and chromosome copy number variations (CNVs) analysis in the detection of leptomeningeal malignancy.

METHODS

Of the 51 patients included in the study, 34 patients were diagnosed with leptomeningeal malignancies, and 17 patients were diagnosed with central nervous system (CNS) inflammatory diseases. The Sayk's spontaneous cell sedimentation technique was employed for CSF cytology. And a well-designed approach utilizing the CSF mNGS-CNVs technique was explored for early diagnosis of leptomeningeal malignancy.

RESULTS

In the tumor group, 28 patients were positive for CSF cytology, and 24 patients were positive for CSF mNGS-CNVs. Sensitivity and specificity of CSF cytology were 82.35% (95% CI: 66.83-92.61%) and 94.12% (95% CI: 69.24-99.69%). In comparison, sensitivity and specificity of CSF mNGS-CNV were 70.59% (95% CI: 52.33-84.29%) and 100% (95% CI: 77.08-100%). There was no significant difference in diagnostic consistency between CSF cytology and mNGS-CNVs (p = 0.18, kappa = 0.650).

CONCLUSIONS

CSF mNGS-CNVs tend to have higher specificity compared with traditional cytology and can be used as a complementary diagnostic method for patients with leptomeningeal malignancies.

Insights into the Clinical, Biological and Therapeutic Impact of Copy Number Alteration in Cancer

Copy number alterations (CNAs), resulting from the gain or loss of genetic material from as little as 50 base pairs or as big as entire chromosome(s), have been associated with many congenital diseases, de novo syndromes and cancer. It is established that CNAs disturb the dosage of genomic regions including enhancers/promoters, long non-coding RNA and gene(s) among others, ultimately leading to an altered balance of key cellular functions. In cancer, CNAs have been associated with almost all steps of the disease: predisposition, initiation, development, maintenance, response to treatment, resistance, and relapse. Therefore, understanding how specific CNAs contribute to tumourigenesis may provide prognostic insight and ultimately lead to the development of new therapeutic approaches to improve patient outcomes. In this review, we provide a snapshot of what is currently known about CNAs and cancer, incorporating topics regarding their detection, clinical impact, origin, and nature, and discuss the integration of innovative genetic engineering strategies, to highlight the potential for targeting CNAs using novel, dosage-sensitive and less toxic therapies for CNA-driven cancer.

PerSEveML: a web-based tool to identify persistent biomarker structure for rare events using an integrative machine learning approach

Omics data sets often pose a computational challenge due to their high dimensionality, large size, and non-linear structures. Analyzing these data sets becomes especially daunting in the presence of rare events. Machine learning (ML) methods have gained traction for analyzing rare events, yet there has been limited exploration of bioinformatics tools that integrate ML techniques to comprehend the underlying biology. Expanding upon our previously developed computational framework of an integrative machine learning approach, we introduce PerSEveML, an interactive web-based tool that uses crowd-sourced intelligence to predict rare events and determine feature selection structures. PerSEveML provides a comprehensive overview of the integrative approach through evaluation metrics that help users understand the contribution of individual ML methods to the prediction process. Additionally, PerSEveML calculates entropy and rank scores, which visually organize input features into a persistent structure of selected, unselected, and fluctuating categories that help researchers uncover meaningful hypotheses regarding the underlying biology. We have evaluated PerSEveML on three diverse biologically complex data sets with extremely rare events from small to large scale and have demonstrated its ability to generate valid hypotheses. PerSEveML is available at https://biostats-shinyr.kumc.edu/PerSEveML/ and https://github.com/sreejatadutta/PerSEveML.

Severity of effect considerations regarding the use of mutation as a toxicological endpoint for risk assessment: A report from the 8th International Workshop on Genotoxicity Testing (IWGT)

Exposure levels without appreciable human health risk may be determined by dividing a point of departure on a dose-response curve (e.g., benchmark dose) by a composite adjustment factor (AF). An "effect severity" AF (ESAF) is employed in some regulatory contexts. An ESAF of 10 may be incorporated in the derivation of a health-based guidance value (HBGV) when a "severe" toxicological endpoint, such as teratogenicity, irreversible reproductive effects, neurotoxicity, or cancer was observed in the reference study. Although mutation data have been used historically for hazard identification, this endpoint is suitable for quantitative dose-response modeling and risk assessment. As part of the 8th International Workshops on Genotoxicity Testing, a sub-group of the Quantitative Analysis Work Group (WG) explored how the concept of effect severity could be applied to mutation. To approach this question, the WG reviewed the prevailing regulatory guidance on how an ESAF is incorporated into risk assessments, evaluated current knowledge of associations between germline or somatic mutation and severe disease risk, and mined available data on the fraction of human germline mutations expected to cause severe disease. Based on this review and given that mutations are irreversible and some cause severe human disease, in regulatory settings where an ESAF is used, a majority of the WG recommends applying an ESAF value between 2 and 10 when deriving a HBGV from mutation data. This recommendation may need to be revisited in the future if direct measurement of disease-causing mutations by error-corrected next generation sequencing clarifies selection of ESAF values.

Single-cell lineage tracing approaches to track kidney cell development and maintenance

The kidney is a complex organ consisting of various cell types. Previous studies have aimed to elucidate the cellular relationships among these cell types in developing and mature kidneys using Cre-loxP-based lineage tracing. However, this methodology falls short of fully capturing the heterogeneous nature of the kidney, making it less than ideal for comprehensively tracing cellular progression during kidney development and maintenance. Recent technological advancements in single-cell genomics have revolutionized lineage tracing methods. Single-cell lineage tracing enables the simultaneous tracing of multiple cell types within complex tissues and their transcriptomic profiles, thereby allowing the reconstruction of their lineage tree with cell state information. Although single-cell lineage tracing has been successfully applied to investigate cellular hierarchies in various organs and tissues, its application in kidney research is currently lacking. This review comprehensively consolidates the single-cell lineage tracing methods, divided into 4 categories (clustered regularly interspaced short palindromic repeat [CRISPR]/CRISPR-associated protein 9 [Cas9]-based, transposon-based, Polylox-based, and native barcoding methods), and outlines their technical advantages and disadvantages. Furthermore, we propose potential future research topics in kidney research that could benefit from single-cell lineage tracing and suggest suitable technical strategies to apply to these topics.

Mutational landscape of HSP family on human breast cancer

Breast cancer (BRCA) is a prevalent malignancy with the highest incidence among females. BRCA can be categorized into five intrinsic molecular subtypes (LumA, LumB, HER2, Basal, and Normal), each characterized by varying molecular and clinical features determined by the expression of intrinsic genes (PAM50). The Heat Shock Protein (HSP) family is composed of 95 genes evolutionary conservated, they have critical roles in proteostasis in both normal and cancerous processes. Many studies have linked HSP to the development and spread of cancer. They modulate the activity of multiple proteins expressed by oncogenes and anti-oncogenes through a range of interactions. In this study, we evaluate the mutational changes that HSP undergoes in BRCA mainly from the TCGA database. We observe that Copy Number Variations (CNV) are the more frequent events analyzed surpassing the occurrence of point mutations, indels, and translation start site mutations. The Basal subtype showcased the highest count of amplified CNV, including subtype-specific changes, whereas the Luminals tumors accumulated the greatest number of deletion CNV. Meanwhile, the HER2 subtype exhibited a comparatively lower frequency of CNV alterations when compared to the other subtypes. This study integrates CNV and expression data, finding associations between these two variables and the influence of CNV on the deregulation of HSP expression. To enhance the role of HSP as a risk predictor in BRCA, we succeeded in identifying CNV profiles as a prognostic marker. We included Artificial Intelligence to improve the clustering of patients, and we achieved a molecular CNV signature as a significant risk factor independent of known classic markers, including molecular subtypes PAM50. This research enhances the comprehension of HSP DNA alterations in BRCA and its relation with predicting the risk of affected individuals providing insights to develop guide personalized treatment strategies.

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.

Genome-Wide Detection of Copy Number Variations and Their Potential Association with Carcass and Meat Quality Traits in Pingliang Red Cattle

Copy number variation (CNV) serves as a significant source of genetic diversity in mammals and exerts substantial effects on various complex traits. Pingliang red cattle, an outstanding indigenous resource in China, possess remarkable breeding value attributed to their tender meat and superior marbling quality. However, the genetic mechanisms influencing carcass and meat quality traits in Pingliang red cattle are not well understood. We generated a comprehensive genome-wide CNV map for Pingliang red cattle using the GGP Bovine 100K SNP chip. A total of 755 copy number variable regions (CNVRs) spanning 81.03 Mb were identified, accounting for approximately 3.24% of the bovine autosomal genome. Among these, we discovered 270 potentially breed-specific CNVRs in Pingliang red cattle, including 143 gains, 73 losses, and 54 mixed events. Functional annotation analysis revealed significant associations between these specific CNVRs and important traits such as carcass and meat quality, reproduction, exterior traits, growth traits, and health traits. Additionally, our network and transcriptome analysis highlighted CACNA2D1, CYLD, UBXN2B, TG, NADK, and ITGA9 as promising candidate genes associated with carcass weight and intramuscular fat deposition. The current study presents a genome-wide CNV map in Pingliang red cattle, highlighting breed-specific CNVRs, and transcriptome findings provide valuable insights into the underlying genetic characteristics of Pingliang red cattle. These results offer potential avenues for enhancing meat quality through a targeted breeding program.

Analysis of copy number variants detected by sequencing in spontaneous abortion

BACKGROUND

The incidence of spontaneous abortion (SA), which affects approximately 15-20% of pregnancies, is the most common complication of early pregnancy. Pathogenic copy number variations (CNVs) are recognized as potential genetic causes of SA. However, CNVs of variants of uncertain significance (VOUS) have been identified in products of conceptions (POCs), and their correlation with SA remains uncertain.

RESULTS

Of 189 spontaneous abortion cases, trisomy 16 was the most common numerical chromosome abnormality, followed by monosomy X. CNVs most often occurred on chromosomes 4 and 8. Gene Ontology and signaling pathway analysis revealed significant enrichment of genes related to nervous system development, transmembrane transport, cell adhesion, and structural components of chromatin. Furthermore, genes within the VOUS CNVs were screened by integrating human placental expression profiles, PhyloP scores, and Residual Variance Intolerance Score (RVIS) percentiles to identify potential candidate genes associated with spontaneous abortion. Fourteen potential candidate genes (LZTR1, TSHZ1, AMIGO2, H1-4, H2BC4, H2AC7, H3C8, H4C3, H3C6, PHKG2, PRR14, RNF40, SRCAP, ZNF629) were identified. Variations in LZTR1, TSHZ1, and H4C3 may contribute to embryonic lethality.

CONCLUSIONS

CNV sequencing (CNV-seq) analysis is an effective technique for detecting chromosomal abnormalities in POCs and identifying potential candidate genes for SA.

Glyoxalase System in Breast and Ovarian Cancers: Role of MEK/ERK/SMAD1 Pathway

The glyoxalase system, comprising GLO1 and GLO2 enzymes, is integral in detoxifying methylglyoxal (MGO) generated during glycolysis, with dysregulation implicated in various cancer types. The MEK/ERK/SMAD1 signaling pathway, crucial in cellular processes, influences tumorigenesis, metastasis, and angiogenesis. Altered GLO1 expression in cancer showcases its complex role in cellular adaptation and cancer aggressiveness. GLO2 exhibits context-dependent functions, contributing to both proapoptotic and antiapoptotic effects in different cancer scenarios. Research highlights the interconnected nature of these systems, particularly in ovarian cancer and breast cancer. The glyoxalase system's involvement in drug resistance and its impact on the MEK/ERK/SMAD1 signaling cascade underscore their clinical significance. Furthermore, this review delves into the urgent need for effective biomarkers, exemplified in ovarian cancer, where the RAGE-ligand pathway emerges as a potential diagnostic tool. While therapeutic strategies targeting these pathways hold promise, this review emphasizes the challenges posed by context-dependent effects and intricate crosstalk within the cellular milieu. Insights into the molecular intricacies of these pathways offer a foundation for developing innovative therapeutic approaches, providing hope for enhanced cancer diagnostics and tailored treatment strategies.

Structural deviations of the posterior fossa and the cerebellum and their cognitive links in a neurodevelopmental deletion syndrome

High-impact genetic variants associated with neurodevelopmental disorders provide biologically-defined entry points for mechanistic investigation. The 3q29 deletion (3q29Del) is one such variant, conferring a 40-100-fold increased risk for schizophrenia, as well as high risk for autism and intellectual disability. However, the mechanisms leading to neurodevelopmental disability remain largely unknown. Here, we report the first in vivo quantitative neuroimaging study in individuals with 3q29Del (N = 24) and neurotypical controls (N = 1608) using structural MRI. Given prior radiology reports of posterior fossa abnormalities in 3q29Del, we focused our investigation on the cerebellum and its tissue-types and lobules. Additionally, we compared the prevalence of cystic/cyst-like malformations of the posterior fossa between 3q29Del and controls and examined the association between neuroanatomical findings and quantitative traits to probe gene-brain-behavior relationships. 3q29Del participants had smaller cerebellar cortex volumes than controls, before and after correction for intracranial volume (ICV). An anterior-posterior gradient emerged in finer grained lobule-based and voxel-wise analyses. 3q29Del participants also had larger cerebellar white matter volumes than controls following ICV-correction and displayed elevated rates of posterior fossa arachnoid cysts and mega cisterna magna findings independent of cerebellar volume. Cerebellar white matter and subregional gray matter volumes were associated with visual-perception and visual-motor integration skills as well as IQ, while cystic/cyst-like malformations yielded no behavioral link. In summary, we find that abnormal development of cerebellar structures may represent neuroimaging-based biomarkers of cognitive and sensorimotor function in 3q29Del, adding to the growing evidence identifying cerebellar pathology as an intersection point between syndromic and idiopathic forms of neurodevelopmental disabilities.

Mapping and functional characterization of structural variation in 1060 pig genomes

BACKGROUND

Structural variations (SVs) have significant impacts on complex phenotypes by rearranging large amounts of DNA sequence.

RESULTS

We present a comprehensive SV catalog based on the whole-genome sequence of 1060 pigs (Sus scrofa) representing 101 breeds, covering 9.6% of the pig genome. This catalog includes 42,487 deletions, 37,913 mobile element insertions, 3308 duplications, 1664 inversions, and 45,184 break ends. Estimates of breed ancestry and hybridization using genotyped SVs align well with those from single nucleotide polymorphisms. Geographically stratified deletions are observed, along with known duplications of the KIT gene, responsible for white coat color in European pigs. Additionally, we identify a recent SINE element insertion in MYO5A transcripts of European pigs, potentially influencing alternative splicing patterns and coat color alterations. Furthermore, a Yorkshire-specific copy number gain within ABCG2 is found, impacting chromatin interactions and gene expression across multiple tissues over a stretch of genomic region of ~200 kb. Preliminary investigations into SV's impact on gene expression and traits using the Pig Genotype-Tissue Expression (PigGTEx) data reveal SV associations with regulatory variants and gene-trait pairs. For instance, a 51-bp deletion is linked to the lead eQTL of the lipid metabolism regulating gene FADS3, whose expression in embryo may affect loin muscle area, as revealed by our transcriptome-wide association studies.

CONCLUSIONS

This SV catalog serves as a valuable resource for studying diversity, evolutionary history, and functional shaping of the pig genome by processes like domestication, trait-based breeding, and adaptive evolution.

Detection and characterization of copy number variation in three differentially-selected Nellore cattle populations

Introduction: Nellore cattle (Bos taurus indicus) is the main beef cattle breed raised in Brazil. This breed is well adapted to tropical conditions and, more recently, has experienced intensive genetic selection for multiple performance traits. Over the past 43 years, an experimental breeding program has been developed in the Institute of Animal Science (IZ, Sertaozinho, SP, Brazil), which resulted in three differentially-selected lines known as Nellore Control (NeC), Nellore Selection (NeS), and Nellore Traditional (NeT). The primary goal of this selection experiment was to determine the response to selection for yearling weight (YW) and residual feed intake (RFI) on Nellore cattle. The main objectives of this study were to: 1) identify copy number variation (CNVs) in Nellore cattle from three selection lines; 2) identify and characterize CNV regions (CNVR) on these three lines; and 3) perform functional enrichment analyses of the CNVR identified. Results: A total of 14,914 unique CNVs and 1,884 CNVRs were identified when considering all lines as a single population. The CNVRs were non-uniformly distributed across the chromosomes of the three selection lines included in the study. The NeT line had the highest number of CNVRs (n = 1,493), followed by the NeS (n = 823) and NeC (n = 482) lines. The CNVRs covered 23,449,890 bp (0.94%), 40,175,556 bp (1.61%), and 63,212,273 bp (2.54%) of the genome of the NeC, NeS, and NeT lines, respectively. Two CNVRs were commonly identified between the three lines, and six, two, and four exclusive regions were identified for NeC, NeS, and NeT, respectively. All the exclusive regions overlap with important genes, such as SMARCD3, SLC15A1, and MAPK1. Key biological processes associated with the candidate genes were identified, including pathways related to growth and metabolism. Conclusion: This study revealed large variability in CNVs and CNVRs across three Nellore lines differentially selected for YW and RFI. Gene annotation and gene ontology analyses of the exclusive CNVRs to each line revealed specific genes and biological processes involved in the expression of growth and feed efficiency traits. These findings contribute to the understanding of the genetic mechanisms underlying the phenotypic differences among the three Nellore selection lines.

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

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

Putative climate adaptation in American pikas (Ochotona princeps) is associated with copy number variation across environmental gradients

Improved understanding of the genetic basis of adaptation to climate change is necessary for maintaining global biodiversity moving forward. Studies to date have largely focused on sequence variation, yet there is growing evidence that suggests that changes in genome structure may be an even more significant source of adaptive potential. The American pika (Ochotona princeps) is an alpine specialist that shows some evidence of adaptation to climate along elevational gradients, but previous work has been limited to single nucleotide polymorphism based analyses within a fraction of the species range. Here, we investigated the role of copy number variation underlying patterns of local adaptation in the American pika using genome-wide data previously collected across the entire species range. We identified 37-193 putative copy number variants (CNVs) associated with environmental variation (temperature, precipitation, solar radiation) within each of the six major American pika lineages, with patterns of divergence largely following elevational and latitudinal gradients. Genes associated (n = 158) with independent annotations across lineages, variables, and/or CNVs had functions related to mitochondrial structure/function, immune response, hypoxia, olfaction, and DNA repair. Some of these genes have been previously linked to putative high elevation and/or climate adaptation in other species, suggesting they may serve as important targets in future studies.

Unravelling the Genetic Landscape of Hemiplegic Migraine: Exploring Innovative Strategies and Emerging Approaches

Migraine is a severe, debilitating neurovascular disorder. Hemiplegic migraine (HM) is a rare and debilitating neurological condition with a strong genetic basis. Sequencing technologies have improved the diagnosis and our understanding of the molecular pathophysiology of HM. Linkage analysis and sequencing studies in HM families have identified pathogenic variants in ion channels and related genes, including CACNA1A, ATP1A2, and SCN1A, that cause HM. However, approximately 75% of HM patients are negative for these mutations, indicating there are other genes involved in disease causation. In this review, we explored our current understanding of the genetics of HM. The evidence presented herein summarises the current knowledge of the genetics of HM, which can be expanded further to explain the remaining heritability of this debilitating condition. Innovative bioinformatics and computational strategies to cover the entire genetic spectrum of HM are also discussed in this review.

Tradeoffs in alignment and assembly-based methods for structural variant detection with long-read sequencing data

Long-read sequencing offers long contiguous DNA fragments, facilitating diploid genome assembly and structural variant (SV) detection. Efficient and robust algorithms for SV identification are crucial with increasing data availability. Alignment-based methods, favored for their computational efficiency and lower coverage requirements, are prominent. Alternative approaches, relying solely on available reads for de novo genome assembly and employing assembly-based tools for SV detection via comparison to a reference genome, demand significantly more computational resources. However, the lack of comprehensive benchmarking constrains our comprehension and hampers further algorithm development. Here we systematically compare 14 read alignment-based SV calling methods (including 4 deep learning-based methods and 1 hybrid method), and 4 assembly-based SV calling methods, alongside 4 upstream aligners and 7 assemblers. Assembly-based tools excel in detecting large SVs, especially insertions, and exhibit robustness to evaluation parameter changes and coverage fluctuations. Conversely, alignment-based tools demonstrate superior genotyping accuracy at low sequencing coverage (5-10×) and excel in detecting complex SVs, like translocations, inversions, and duplications. Our evaluation provides performance insights, highlighting the absence of a universally superior tool. We furnish guidelines across 31 criteria combinations, aiding users in selecting the most suitable tools for diverse scenarios and offering directions for further method development.

Identification of a rare copy number polymorphic gain at 3q12.2 with candidate genes for familial endometriosis

Endometriosis is a complex disease that affects 10-15% of women of reproductive age. Familial studies show that relatives of affected patients have a higher risk of developing the disease, implicating a genetic role for this disorder. Little is known about the impact of germline genomic copy number variant (CNV) polymorphisms on the heredity of the disease. In this study, we describe a rare CNV identified in two sisters with familial endometriosis, which contain genes that may increase the susceptibility and progression of this disease. We investigated the presence of CNVs from the endometrium and blood of the sisters with endometriosis and normal endometrium of five women as controls without the disease using array-CGH through the Agilent 2x400K platform. We excluded common CNVs that were present in the database of genomic variation. We identified, in both sisters, a rare CNV gain affecting 113kb at band 3q12.2 involving two candidate genes: ADGRG7 and TFG. The CNV gain was validated by qPCR. ADGRG7 is located at 3q12.2 and encodes a G protein-coupled receptor influencing the NF-kappaβ pathway. TFG participates in chromosomal translocations associated with hematologic tumor and soft tissue sarcomas, and is also involved in the NF-kappa B pathway. The CNV gain in this family provides a new candidate genetic marker for future familial endometriosis studies. Additional longitudinal studies of affected families must confirm any associations between this rare CNV gain and genes involved in the NF-kappaβ pathway in predisposition to endometriosis.

Optical Genome Mapping Reveals Genomic Alterations upon Gene Editing in hiPSCs: Implications for Neural Tissue Differentiation and Brain Organoid Research

Genome editing, notably CRISPR (cluster regularly interspaced short palindromic repeats)/Cas9 (CRISPR-associated protein 9), has revolutionized genetic engineering allowing for precise targeted modifications. This technique's combination with human induced pluripotent stem cells (hiPSCs) is a particularly valuable tool in cerebral organoid (CO) research. In this study, CRISPR/Cas9-generated fluorescently labeled hiPSCs exhibited no significant morphological or growth rate differences compared with unedited controls. However, genomic aberrations during gene editing necessitate efficient genome integrity assessment methods. Optical genome mapping, a high-resolution genome-wide technique, revealed genomic alterations, including chromosomal copy number gain and losses affecting numerous genes. Despite these genomic alterations, hiPSCs retain their pluripotency and capacity to generate COs without major phenotypic changes but one edited cell line showed potential neuroectodermal differentiation impairment. Thus, this study highlights optical genome mapping in assessing genome integrity in CRISPR/Cas9-edited hiPSCs emphasizing the need for comprehensive integration of genomic and morphological analysis to ensure the robustness of hiPSC-based models in cerebral organoid research.

Independent expansion, selection and hypervariability of the TBC1D3 gene family in humans

TBC1D3 is a primate-specific gene family that has expanded in the human lineage and has been implicated in neuronal progenitor proliferation and expansion of the frontal cortex. The gene family and its expression have been challenging to investigate because it is embedded in high-identity and highly variable segmental duplications. We sequenced and assembled the gene family using long-read sequencing data from 34 humans and 11 nonhuman primate species. Our analysis shows that this particular gene family has independently duplicated in at least five primate lineages, and the duplicated loci are enriched at sites of large-scale chromosomal rearrangements on chromosome 17. We find that most humans vary along two TBC1D3 clusters where human haplotypes are highly variable in copy number, differing by as many as 20 copies, and structure (structural heterozygosity 90%). We also show evidence of positive selection, as well as a significant change in the predicted human TBC1D3 protein sequence. Lastly, we find that, despite multiple duplications, human TBC1D3 expression is limited to a subset of copies and, most notably, from a single paralog group: TBC1D3-CDKL. These observations may help explain why a gene potentially important in cortical development can be so variable in the human population.

Understanding the Genetic and Non-Genetic Interconnections in the Aetiology of Syndromic Congenital Heart Disease: An Updated Review: Part 2

PURPOSE OF REVIEW

Approximately 30% of syndromic cases diagnosed with CHD, which lure us to further investigate the molecular and clinical challenges behind syndromic CHD (sCHD). The aetiology of sCHD in a majority of cases remains enigmatic due to involvement of multiple factors, namely genetic, epigenetic and environmental modifiable risk factors for the development of the disease. Here, we aim to update the role of genetic contributors including chromosomal abnormalities, copy number variations (CNVs) and single gene mutations in cardiac specific genes, maternal lifestyle conditions, environmental exposures and epigenetic modifiers in causing CHD in different genetic syndromes.

RECENT FINDINGS

The exact aetiology of sCHD is still unknown. With the advancement of next-generation technologies including WGS, WES, transcriptome, proteome and methylome study, numerous novel genes and pathways have been identified. Moreover, our recent knowledge regarding epigenetic and environmental regulation during cardiogenesis is still evolving and may solve some of the mystery behind complex sCHD. Here, we focus to understand how the complex combination of genetic, environmental and epigenetic factors interact to interfere with developmental pathways, culminating into cardiac and extracardiac defects in sCHD.

Ethnic and functional differentiation of copy number polymorphisms in Tunisian and HapMap population unveils insights on genome organizational plasticity

Admixture mapping has been useful in identifying genetic variations linked to phenotypes, adaptation and diseases. Copy number variations (CNVs) represents genomic structural variants spanning large regions of chromosomes reaching several megabases. In this investigation, the "Canary" algorithm was applied to 102 Tunisian samples and 991 individuals from eleven HapMap III populations to genotype 1279 copy number polymorphisms (CNPs). In this present work, we investigate the Tunisian population structure using the CNP makers previously identified among Tunisian. The study revealed that Sub-Saharan African populations exhibited the highest diversity with the highest proportions of allelic CNPs. Among all the African populations, Tunisia showed the least diversity. Individual ancestry proportions computed using STRUCTURE analysis revealed a major European component among Tunisians with lesser contribution from Sub-Saharan Africa and Asia. Population structure analysis indicated the genetic proximity with Europeans and noticeable distance from the Sub-Saharan African and East Asian clusters. Seven genes harbouring Tunisian high-frequent CNPs were identified known to be associated with 9 Mendelian diseases and/or phenotypes. Functional annotation of genes under selection highlighted a noteworthy enrichment of biological processes to receptor pathway and activity as well as glutathione metabolism. Additionally, pathways of potential concern for health such as drug metabolism, infectious diseases and cancers exhibited significant enrichment. The distinctive genetic makeup of the Tunisians might have been influenced by various factors including natural selection and genetic drift, resulting in the development of distinct genetic variations playing roles in specific biological processes. Our research provides a justification for focusing on the exclusive genome organization of this population and uncovers previously overlooked elements of the genome.

Analysis of the Association between Copy Number Variation and Ventricular Fibrillation in ST-Elevation Acute Myocardial Infarction

Sudden cardiac death due to ventricular fibrillation (VF) during ST-elevation acute myocardial infarction (STEAMI) significantly contributes to cardiovascular-related deaths. Although VF has been linked to genetic factors, variations in copy number variation (CNV), a significant source of genetic variation, have remained largely unexplored in this context. To address this knowledge gap, this study performed whole exome sequencing analysis on a cohort of 39 patients with STEAMI who experienced VF, aiming to elucidate the role of CNVs in this pathology. The analysis revealed CNVs in the form of duplications in the PARP2 and TTC5 genes as well as CNVs in the form of deletions in the MUC15 and PPP6R1 genes, which could potentially serve as risk indicators for VF during STEAMI. The analysis also underscores notable CNVs with an average gene copy number equal to or greater than four in DEFB134, FCGR2C, GREM1, PARM1, SCG5, and UNC79 genes. These findings provide further insight into the role of CNVs in VF in the context of STEAMI.

Identify Candidate Genes Associated with the Weight and Egg Quality Traits in Wenshui Green Shell-Laying Chickens by the Copy Number Variation-Based Genome-Wide Association Study

Copy number variation (CNV), as an essential source of genetic variation, can have an impact on gene expression, genetic diversity, disease susceptibility, and species evolution in animals. To better understand the weight and egg quality traits of chickens, this paper aimed to detect CNVs in Wenshui green shell-laying chickens and conduct a copy number variation regions (CNVRs)-based genome-wide association study (GWAS) to identify variants and candidate genes associated with their weight and egg quality traits to support related breeding efforts. In our paper, we identified 11,035 CNVRs in Wenshui green shell-laying chickens, which collectively spanned a length of 13.1 Mb, representing approximately 1.4% of its autosomal genome. Out of these CNVRs, there were 10,446 loss types, 491 gain types, and 98 mixed types. Notably, two CNVRs showed significant correlations with egg quality, while four CNVRs exhibited significant associations with body weight. These significant CNVRs are located on chromosome 4. Further analysis identified potential candidate genes that influence weight and egg quality traits, including FAM184B, MED28, LAP3, ATOH8, ST3GAL5, LDB2, and SORCS2. In this paper, the CNV map of the Wenshui green shell-laying chicken genome was constructed for the first time through population genotyping. Additionally, CNVRs can be employed as molecular markers to genetically improve chickens' weight and egg quality traits.