Genomic Variants Research Articles

Exploring the interplay between colorectal cancer subtypes genomic variants and cellular morphology: A deep-learning approach.

Molecular subtypes of colorectal cancer (CRC) significantly influence treatment decisions. While convolutional neural networks (CNNs) have recently been introduced for automated CRC subtype identification using H&E stained histopathological images, the correlation between CRC subtype genomic variants and their corresponding cellular morphology expressed by their imaging phenotypes is yet to be fully explored. The goal of this study was to determine such correlations by incorporating genomic variants in CNN models for CRC subtype classification from H&E images. We utilized the publicly available TCGA-CRC-DX dataset, which comprises whole slide images from 360 CRC-diagnosed patients (260 for training and 100 for testing). This dataset also provides information on CRC subtype classifications and genomic variations. We trained CNN models for CRC subtype classification that account for potential correlation between genomic variations within CRC subtypes and their corresponding cellular morphology patterns. We assessed the interplay between CRC subtypes' genomic variations and cellular morphology patterns by evaluating the CRC subtype classification accuracy of the different models in a stratified 5-fold cross-validation experimental setup using the area under the ROC curve (AUROC) and average precision (AP) as the performance metrics. The CNN models that account for potential correlation between genomic variations within CRC subtypes and their cellular morphology pattern achieved superior accuracy compared to the baseline CNN classification model that does not account for genomic variations when using either single-nucleotide-polymorphism (SNP) molecular features (AUROC: 0.824±0.02 vs. 0.761±0.04, p<0.05, AP: 0.652±0.06 vs. 0.58±0.08) or CpG-Island methylation phenotype (CIMP) molecular features (AUROC: 0.834±0.01 vs. 0.787±0.03, p<0.05, AP: 0.687±0.02 vs. 0.64±0.05). Combining the CNN models account for variations in CIMP and SNP further improved classification accuracy (AUROC: 0.847±0.01 vs. 0.787±0.03, p = 0.01, AP: 0.68±0.02 vs. 0.64±0.05). The improved accuracy of CNN models for CRC subtype classification that account for potential correlation between genomic variations within CRC subtypes and their corresponding cellular morphology as expressed by H&E imaging phenotypes may elucidate the biological cues impacting cancer histopathological imaging phenotypes. Moreover, considering CRC subtypes genomic variations has the potential to improve the accuracy of deep-learning models in discerning cancer subtype from histopathological imaging data.

Novel evidence of CNV deletion in KCTD13 related to the severity of isolated hypospadias in Chinese population.

CNV in KCTD13 has been identified to influence androgen receptor function via its changes in gene dosage, which might contribute to hypospadias. However, there is lack of population-level evidence to assess the contribution of KCTD13 CNV to hypospadias. 349 isolated hypospadias patients were recruited and their genotyping was performed using real-time qPCR. We use Database of Genomic Variants (DGV) and CNV calls from SNP-array intensity data in 1,008 Chinese healthy men as reference. 11.17% of patients were identified to have KCTD13 CNV deletion, significantly higher than 0.05% in DGV (P < 0.001), but no cases found to have CNV duplication. Meanwhile, no CNV calls encompassing KCTD13 region were detected in Chinese healthy men. Incidence of KCTD13 CNV deletion was significantly increased with the severity of hypospadias, P _trend = 9.00 × 10-6. Compared to distal hypospadias, ORs for the proximal and midshaft were 10.07 (2.91-34.84) and 6.08 (1.69-21.84) respectively. In addition, the association between genital characteristics (stretched penile length and glans width) and KCTD13 CNV showed no significance in hypospadias children (P > 0.05). We demonstrate KCTD13 CNV deletion is strongly associated with hypospadias and its severity, but duplication is not, characterizing KCTD13 genetic variation in more detail than previously described.

Lynch Syndrome-associated Genomic Variants.

Lynch Syndrome, a hereditary disorder characterized by germline mutations in mismatch repair (MMR) genes, is a major contributor to colorectal cancers. It has also been identified in endometrial cancer. Despite the established role of MMR deficiency in tumorigenesis, the specific genomic alterations driving Lynch syndrome-associated endometrial cancer, and their overlap with colorectal cancer, remain incompletely understood. This study aims to fill this gap by performing a detailed comparative analysis of germline and somatic mutations in endometrial cancer within the context of Lynch syndrome. We conducted whole exome sequencing on matched germline and somatic DNA from 13 patients diagnosed with Lynch syndrome-associated endometrial cancer. High-depth sequencing was performed, followed by rigorous bioinformatics analysis to identify and annotate variants, focusing on their potential pathogenicity and relevance to both endometrial and colorectal cancer. Our analysis revealed 1,118 germline and 14,051 somatic variants, with 493 variants common to both. Recurrent pathogenic mutations in MLH1, MSH2, and MSH6 were confirmed, highlighting their critical role in Lynch syndrome. Notably, frequent somatic mutations in the PIK3CA and PTEN genes were identified, implicating the PI3K/AKT/mTOR pathway as a key oncogenic driver in these cancers. Additionally, novel somatic mutations in genes related to the extracellular matrix such as FBN1 and SPARC were uncovered, suggesting a possible unique role in endometrial tumor progression. This study provides new insights into the molecular basis of Lynch syndrome-associated endometrial cancer, emphasizing the overlap in oncogenic pathways with colorectal cancer. The discovery of shared and unique genetic mutations highlights the importance of developing combined treatment strategies and suggests that targeting these specific mutations could improve therapy for patients with Lynch syndrome-associated cancers.

Whole-genome de novo sequencing reveals genomic variants associated with differences of sex development in SRY negative pigs

BackgroundDifferences of sex development (DSD) are congenital conditions in which chromosomal, gonadal, or phenotypic sex is atypical. In more than 50% of human DSD cases, a molecular diagnosis is not available. In intensively farmed pig populations, the incidence of XX DSD pigs is relatively high, leading to economic losses for pig breeders. Interestingly, in the majority of 38, XX DSD pigs, gonads still develop into testis-like structures or ovotestes despite the absence of the testis-determining gene (SRY). However, the current understanding of the molecular background of XX DSD pigs remains limited.MethodsAnatomical and histological characteristics of XX DSD pigs were analysed using necropsy and HE staining. We employed whole-genome sequencing (WGS) with 10× Genomics technology and used de novo assembly methodology to study normal female and XX DSD pigs. Finally, the identified variants were validated in 32 XX DSD pigs, and the expression levels of the candidate variants in the gonads of XX DSD pigs were further examined.ResultsXX DSD pigs are characterised by the intersex reproductive organs and the absence of germ cells in the seminiferous tubules of the gonads. We identified 4,950 single-nucleotide polymorphisms (SNPs) from non-synonymous mutations in XX DSD pigs. Cohort validation results highlighted two specific SNPs, “c.218T > C” in the “Interferon-induced transmembrane protein 1 gene (IFITM1)” and “c.1043C > G” in the “Newborn ovary homeobox gene (NOBOX)”, which were found exclusively in XX DSD pigs. Moreover, we verified 14 candidate structural variants (SVs) from 1,474 SVs, identifying a 70 bp deletion fragment in intron 5 of the WW domain-containing oxidoreductase gene (WWOX) in 62.5% of XX DSD pigs. The expression levels of these three candidate genes in the gonads of XX DSD pigs were significantly different from those of normal female pigs.ConclusionThe nucleotide changes of IFITM1 (c.218T > C), NOBOX (c.1043 C > G), and a 70 bp deletion fragment of the WWOX were the most dominant variants among XX DSD pigs. This study provides a theoretical basis for better understanding the molecular background of XX DSD pigs.Plain language summaryDSD are conditions affecting development of the gonads or genitalia. These disorders can happen in many different types of animals, including pigs, goats, dogs, and people. In people, DSD happens in about 0.02–0.13% of births, and in pigs, the rate is between 0.08% and 0.75%. Pigs have a common type of DSD where the animal has female chromosomes (38, XX) but no SRY gene, which is usually found on the Y chromosome in males. XX DSD pigs may look like both males and females on the outside and have testis-like or ovotestis (a mix of ovary and testis) gonads inside. XX DSD pigs often lead to not being able to have piglets, slower growth, lower chance of survival, and poorer meat quality. Here, we used a method called whole-genome de novo sequencing to look for variants in the DNA of XX DSD pigs. We then checked these differences in a larger group of pigs. Our results reveal the nucleotide changes in IFITM1 (c.218T > C), NOBOX (c.1043 C > G), and a 70 bp deletion fragment in intron 5 of the WWOX, all linked to XX DSD pigs. The expression levels of these three genes were also different in the gonads of XX DSD pigs compared to normal female pigs. These variants are expected to serve as valuable molecular markers for XX DSD pigs. Because pigs are a lot like humans in their genes, physiology, and body structure, this research could help us learn more about what causes DSD in people.

Genomic insights from a deeply phenotyped highly consanguineous neurodevelopmental disorders cohort

PurposeThe genetic underpinning of neurodevelopmental disorders (NDDs) in diverse ethnic populations, especially those with high rates of consanguinity, remains largely unexplored. Here, we aim to elucidate genomic insight from a 576 person well-phenotyped and highly consanguineous (16%) NDD cohort. MethodsWe used chromosomal microarray (CMA; N:247) and exome sequencing (ES; N:127) combined CMA, ES (N:202), and long-read genome sequencing to identify genetic etiology. Deep clinical multivariate data were coupled with genomic variants for stratification analysis. ResultsGenetic diagnosis rates were 17% with CMA, 29.92% with ES, and 37.13% with combined CMA and ES. Notably, children of consanguineous parents showed a significantly higher diagnostic yield (P < .01) compared with those from nonconsanguineous parents. Among the ES-identified pathogenic variants, 36.19% (38/105) were novel, implicating 35 unique genes. Long-read sequencing of seizure participants unresolved by combined test identified expanded FMR1 trinucleotide repeats. Additionally, we identified 2 recurrent X-linked variants in the G6PD in 3.65% (12/329) of NDD participants. These variants were absent in large-population control cohorts and cohort comprising neurodevelopmental and neuropsychiatric populations of European descendants, indicating a possible associated risk factor potentially resulting from ancient genetic drift. ConclusionThis study unveils unique clinical and genomic insights from a consanguinity rich Bangladeshi NDD cohort, highlighting a strong association of G6PD with NDD in this population.

Functional characterization vs in silico prediction for TBX5 missense and splice variants in Holt-Oram syndrome

PurposePredicting effects of genomic variants has become a real challenge in the diagnosis of rare human diseases. Holt-Oram syndrome is an autosomal condition characterized by the association of radial and heart defects, due to variants in TBX5. Most variants are predicted to be truncating and result in haploinsufficiency. The pathogenicity of missense or splice variants is harder to demonstrate. MethodsFourteen TBX5 variants of uncertain significance (5 missense, 9 splice) and 6 likely pathogenic missense variants were selected for functional testing, depending on the variant-type (immunolocalization, western blot, reporter assays, minigene splice assays, and RT-PCR). Results were compared with in silico predictions. ResultsFunctional tests allowed to reclassify 9/14 variants of uncertain significance in TBX5 as likely pathogenic, confirming their role in Holt-Oram syndrome. We demonstrated loss of function (n = 8) or gain of function (n = 1) for 9 of the 11 missense variants, whereas no functional impact was shown for the 2 variants: p.(Gly195Ala) and p.(Ser261Cys), as suggested by contradictory predictions of in silico approaches. Of 9 splice variants predicted to affect splicing by SpliceAI, we observed partial or complete exon skipping (n = 6), intron retention (n = 2) or exon shortening (n = 1), inducing frame shifting with premature stop codons. ConclusionBioinformatic and biological approaches are complementary, together with a good knowledge of clinical conditions, for accurate American College of Medical Genetics and Genomics classification in human rare diseases.

Genomic variants associated with inborn errors in carbohydrate metabolism in southwestern Colombia

Introduction: Carbohydrate Inborn Errors of Metabolism (IEMs) result from disruption of the catabolic or anabolic pathways of different carbohydrates, fructose, galactose and glycogen being the most common and belong to a heterogeneous group of disorders that may be inherited or may occur as a result of spontaneous genetic variants. In IEM, there are altered carbohydrate pathways, both catabolic and anabolic pathways, including fructose, galactose and glycogen metabolism, resulting in a heterogeneous group of disorders. However, data on these pathologies in Colombia are scarce. The aim of our study was to identify genomic variants associated with carbohydrate IEM in the southwestern Colombian population lacking clinical diagnosis. Results: We performed a cross-sectional study, sequencing 320 exomes and classifying variants according to standard guidelines. We identified 286 variants, including 206 new variants and 73 benign or probably benign variants. Notably, six variants in genes such as GALT, GAK1, ALDOB, GAA and SLC2A1 were of uncertain significance, and one pathogenic variant in the GALT gene was associated with classic galactosemia. Interestingly, 18% were intronic, 5% missense, 10% synonymous, and 67% unreported variants. Conclusions: These findings highlight the need for early diagnostic programs to implement targeted treatments, including transdisciplinary management to minimize morbidity and mortality. Genetic counseling and risk education are crucial, facilitating anticipatory and preventive medicine approaches, thus advancing precision medicine.

VCAT: an integrated variant function annotation tools.

The development of sequencing technology has promoted discovery of variants in the human genome. Identifying functions of these variants is important for us to link genotype to phenotype, and to diagnose diseases. However, it usually requires researchers to visit multiple databases. Here, we presented a one-stop webserver for variant function annotation tools (VCAT, https://biomed.nscc-gz.cn/zhaolab/VCAT/ ) that is the first one connecting variant to functions via the epigenome, protein, drug and RNA. VCAT is also the first one to make all annotations visualized in interactive charts or molecular structures. VCAT allows users to upload data in VCF format, and download results via a URL. Moreover, VCAT has annotated a huge number (1,262,041,068) of variants collected from dbSNP, 1000 Genomes projects, gnomAD, ICGC, TCGA, and HPRC Pangenome project. For these variants, users are able to searcher their functions, related diseases and drugs from VCAT. In summary, VCAT provides a one-stop webserver to explore the potential functions of human genomic variants including their relationship with diseases and drugs.

Uncovering structural variants in Creole cattle from Guadeloupe and their impact on environmental adaptation through whole genome sequencing.

Structural variants play an important role in evolutionary processes. Besides, they constitute a large source of inter individual genetic variation that might represent a major factor in the aetiology of complex, multifactorial traits. Their importance in adaptation is becoming increasingly evident in literature. Yet, the characterization of the genomic landscape of structural variants in local breeds remains scarce to date. Herein, we investigate patterns and gene annotation of structural variants in the Creole cattle from Guadeloupe breed using whole genome sequences from 23 bulls representative of the population. In total, we detected 32821 ascertained SV defining 15258 regions, representing ~ 17% of the Creole cattle genome. Among these, 6639 regions have not been previously reported in the Database of Genomic Variants archive. Average number of structural variants detected per individual in the studied population is in the same order of magnitude of that observed in indicine populations and higher than that reported in taurine breeds. We observe an important within-individual variability where approximately half of the detected structural variants have low frequency (MAF < 0.25). Most of the detected structural variants (55%) occurred in intergenic regions. Genic structural variants overlapped with 7793 genes and the predicted effect of most of them is ranked as "modifier". Among the structural variants that were predicted to have a high functional impact on the protein, a 5.5 Kb in length, highly frequent deletion on chromosome 2, affects ALPI, a gene associated with the interaction between gut microbiota and host immune system. The 6639 newly identified structural variants regions include three deletions and three duplications shared by more than 80% of individuals that are significantly enriched for genes related to tRNA threonylcarbamoyladenosine metabolic process, important for temperature adaptation in thermophilic organisms, therefore suggesting a potential role in the thermotolerance of Creole cattle from Guadeloupe cattle to tropical climate. Overall, highly frequent structural variants that are specific to the Creole cattle population encompass olfactory receptor and immunity genes as well as genes involved in muscle tone, muscle development and contraction. Beyond mapping and characterizing structural variants in the Creole cattle from Guadeloupe breed, this study provides valuable information for a better understanding of the potential role of chromosomal rearrangements in adaptive traits in cattle.

Switch-like Gene Expression Modulates Disease Susceptibility.

A fundamental challenge in biomedicine is understanding the mechanisms predisposing individuals to disease. While previous research has suggested that switch-like gene expression is crucial in driving biological variation and disease susceptibility, a systematic analysis across multiple tissues is still lacking. By analyzing transcriptomes from 943 individuals across 27 tissues, we identified 1,013 switch-like genes. We found that only 31 (3.1%) of these genes exhibit switch-like behavior across all tissues. These universally switch-like genes appear to be genetically driven, with large exonic genomic structural variants explaining five (~18%) of them. The remaining switch-like genes exhibit tissue-specific expression patterns. Notably, tissue-specific switch-like genes tend to be switched on or off in unison within individuals, likely under the influence of tissue-specific master regulators, including hormonal signals. Among our most significant findings, we identified hundreds of concordantly switched-off genes in the stomach and vagina that are linked to gastric cancer (41-fold, p<10-4) and vaginal atrophy (44-fold, p<10-4), respectively. Experimental analysis of vaginal tissues revealed that low systemic levels of estrogen lead to a significant reduction in both the epithelial thickness and the expression of the switch-like gene ALOX12. We propose a model wherein the switching off of driver genes in basal and parabasal epithelium suppresses cell proliferation therein, leading to epithelial thinning and, therefore, vaginal atrophy. Our findings underscore the significant biomedical implications of switch-like gene expression and lay the groundwork for potential diagnostic and therapeutic applications.

Genomic structural variants analysis in leukemia by a novel cytogenetic technique: Optical genome mapping.

Genomic structural variants (SVs) play a pivotal role in driving the evolution of hematologic malignancies, particularly in leukemia, in which genetic abnormalities are crucial features. Detecting SVs is essential for achieving precise diagnosis and prognosis in these cases. Karyotyping, often complemented by fluorescence insitu hybridization and/or chromosomal microarray analysis, provides standard diagnostic outcomes for various types of SVs in front-line testing for leukemia. Recently, optical genome mapping (OGM) has emerged as a promising technique due to its ability to detect all SVs identified by other cytogenetic methods within one single assay. Furthermore, OGM has revealed additional clinically significant SVs in various clinical laboratories, underscoring its considerable potential for enhancing front-line testing in cases of leukemia. This review aims to elucidate the principles of conventional cytogenetic techniques and OGM, with a focus on the technical performance of OGM and its applications in diagnosing and prognosticating myelodysplastic syndromes, acute myeloid leukemia, acute lymphoblastic leukemia, and chronic lymphocytic leukemia.

Perinatal outcomes after a prenatal diagnosis of a fetal copy number variant: a retrospective population-based cohort study

BackgroundThere are no established guidelines for the follow up of infants born after a prenatal diagnosis of a genomic copy number variant (CNV), despite their increased risk of developmental issues. The aims of this study were (i) to determine the perinatal outcomes of fetuses diagnosed with and without a CNV, and (ii) to establish a population-based paediatric cohort for long term developmental follow up.MethodsAn Australian state-wide research database was screened for pregnant individuals who had a prenatal chromosomal microarray (CMA) between 2013–2019 inclusive. Following linkage to laboratory records and clinical referrer details, hospital records were manually reviewed for study eligibility. Eligible participants were mother–child pairs where the pregnancy resulted in a livebirth, the mother was able to provide informed consent in English (did not require a translator) and the mother was the primary caregiver for the child at hospital discharge after birth. Research invitations were sent by registered post at an average of six years after the prenatal diagnostic test. Statistical analysis was performed in Stata17.ResultsOf 1832 prenatal records examined, 1364 (74.5%) mother–child pairs were eligible for recruitment into the follow up cohort. Of the 468 ineligible, 282 (60.3%) had ‘no live pregnancy outcome’ (209 terminations of pregnancy (TOP) and 73 miscarriages, stillbirths, and infant deaths), 157 (33.5%) required a translator, and 29 (6.2%) were excluded for other reasons. TOP rates varied by the type of fetal CNV detected: 49.3% (109/221) for pathogenic CNVs, 18.2% (58/319) for variants of uncertain significance and 3.3% (42/1292) where no clinically significant CNV was reported on CMA. Almost 77% of invitation letters were successfully delivered (1047/1364), and the subsequent participation rate in the follow up cohort was 19.2% (201/1047).ConclusionsThis study provides Australia’s first population-based data on perinatal outcomes following prenatal diagnostic testing with CMA. The relatively high rates of pregnancy loss for those with a prenatal diagnosis of a CNV presented a challenge for establishing a paediatric cohort to examine long term outcomes. Recruiting a mother–child cohort via prenatal ascertainment is a complex and resource-intensive process, but an important step in understanding the impact of a CNV diagnosis in pregnancy and beyond.Trial registrationACTRN12620000446965p; Registered on April 6, 2020.

Insertions and Deletions: Computational Methods, Evolutionary Dynamics, and Biological Applications.

Insertions and deletions constitute the second most important source of natural genomic variation. Insertions and deletions make up to 25% of genomic variants in humans and are involved in complex evolutionary processes including genomic rearrangements, adaptation, and speciation. Recent advances in long-read sequencing technologies allow detailed inference of insertions and deletion variation in species and populations. Yet, despite their importance, evolutionary studies have traditionally ignored or mishandled insertions and deletions due to a lack of comprehensive methodologies and statistical models of insertions and deletion dynamics. Here, we discuss methods for describing insertions and deletion variation and modeling insertions and deletions over evolutionary time. We provide practical advice for tackling insertions and deletions in genomic sequences and illustrate our discussion with examples of insertions and deletion-induced effects in human and other natural populations and their contribution to evolutionary processes. We outline promising directions for future developments in statistical methodologies that would allow researchers to analyze insertions and deletion variation and their effects in large genomic data sets and to incorporate insertions and deletions in evolutionary inference.

Shared germline genomic variants in two patients with double primary gastrointestinal stromal tumours (GISTs)

BackgroundGastrointestinal stromal tumours (GISTs) are prevalent mesenchymal tumours of the gastrointestinal tract, commonly exhibiting structural variations in KIT and PDGFRA genes. While the mutational profiling of somatic tumours is well...

Pharmacokinetics and Pharmacogenomics of Ribociclib in Black Patients with Metastatic Breast Cancer: The LEANORA study.

Underrepresented populations' participation in clinical trials remains limited, and the potential impact of genomic variants on drug metabolism remains elusive. This study aimed to assess the pharmacokinetics (PK) and pharmacogenomics (PGx) of ribociclib in self-identified Black women with hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2) advanced breast cancer. LEANORA (NCT04657679) was a prospective, observational, multicenter cohort study involving 14 Black women. PK and PGx were evaluated using tandem mass spectrometry and PharmacoScan™ microarray (including CYP3A5*3 , *6 , and *7 ). CYP3A5 phenotypes varied among participants: 7 poor metabolizers (PM), 6 intermediate metabolizers (IM), and one normal metabolizer (NM). The area-under-the-curve did not significantly differ between PMs (39,230 hr*ng/mL) and IM/NMs (43,546 hr*ng/mL; p = 0.38). The incidence of adverse events (AEs) was also similar. We found no association between CYP3A5 genotype and ribociclib exposure. Continued efforts are needed to include diverse populations in clinical trials to ensure equitable treatment outcomes.

Evaluation of deep learning for predicting rice traits using structural and single-nucleotide genomic variants

BackgroundStructural genomic variants (SVs) are prevalent in plant genomes and have played an important role in evolution and domestication, as they constitute a significant source of genomic and phenotypic variability. Nevertheless, most methods in quantitative genetics focusing on crop improvement, such as genomic prediction, consider only Single Nucleotide Polymorphisms (SNPs). Deep Learning (DL) is a promising strategy for genomic prediction, but its performance using SVs and SNPs as genetic markers remains unknown.ResultsWe used rice to investigate whether combining SVs and SNPs can result in better trait prediction over SNPs alone and examine the potential advantage of Deep Learning (DL) networks over Bayesian Linear models. Specifically, the performances of BayesC (considering additive effects) and a Bayesian Reproducible Kernel Hilbert space (RKHS) regression (considering both additive and non-additive effects) were compared to those of two different DL architectures, the Multilayer Perceptron, and the Convolution Neural Network, to explore their prediction ability by using various marker input strategies. We found that exploiting structural and nucleotide variation slightly improved prediction ability on complex traits in 87% of the cases. DL models outperformed Bayesian models in 75% of the studied cases, considering the four traits and the two validation strategies used. Finally, DL systematically improved prediction ability of binary traits against the Bayesian models.ConclusionsOur study reveals that the use of structural genomic variants can improve trait prediction in rice, independently of the methodology used. Also, our results suggest that Deep Learning (DL) networks can perform better than Bayesian models in the prediction of binary traits, and in quantitative traits when the training and target sets are not closely related. This highlights the potential of DL to enhance crop improvement in specific scenarios and the importance to consider SVs in addition to SNPs in genomic selection.

Mitochondrial genome variants associated with amyotrophic lateral sclerosis and their haplogroup distribution.

Amyotrophic lateral sclerosis (ALS) may be familial or sporadic, and twin studies have revealed that even sporadic forms have a significant genetic component. Variants in 55 nuclear genes have been associated with ALS and although mitochondrial dysfunction is observed in ALS, variants in mitochondrial genomes (mitogenomes) have not yet been tested for association with ALS. The aim of this study was to determine whether mitogenome variants are associated with ALS. We conducted a genome-wide association study (GWAS) in mitogenomes of 1965 ALS patients and 2547 controls. We identified 51 mitogenome variants with p values <10-7, of which 13 had odds ratios (ORs) >1, in genes RNR1, ND1, CO1, CO3, ND5, ND6, and CYB, while 38 variants had OR <1 in genes RNR1, RNA2, ND1, ND2, CO2, ATP8, ATP6, CO3, ND3, ND4, ND5, ND6, and CYB. The frequencies of haplogroups H, U, and L, the most frequent in our ALS data set, were the same in different onset sites (bulbar, limb, spinal, and axial). Also, intra-haplogroup GWAS revealed unique ALS-associated variants in haplogroups L and U. Our study shows that mitogenome single nucleotide variants (SNVs) are associated with ALS and suggests that these SNVs could be included in routine genetic testing for ALS and that mitochondrial replacement therapy has the potential to serve as a basis for ALS treatment.

Whole genome sequencing enhances molecular diagnosis of primary ciliary dyskinesia.

Primary ciliary dyskinesia (PCD) is a genetic disorder affecting motile cilia. Most cases are inherited recessively, due to variants in >50 genes that result in abnormal or absent motile cilia. This leads to chronic upper and lower airway disease, subfertility, and laterality defects. Given overlapping clinical features and genetic heterogeneity, diagnosis can be difficult and often occurs late. Of those tested an estimated 30% of genetically screened PCD patients still lack a molecular diagnosis. A molecular diagnosis allows for appropriate clinical management including prediction of phenotypic features correlated to genotype. Here, we aimed to identify how readily a genetic diagnosis could be made using whole genome sequencing (WGS) to facilitate identification of pathogenic variants in known genes as well as novel PCD candidate genes. WGS was used to screen for pathogenic variants in eight patients with PCD. 7/8 cases had homozygous or biallelic variants in DNAH5, DNAAF4 or DNAH11 classified as pathogenic or likely pathogenic. Three identified variants were deletions, ranging from 3 to 13 kb, for which WGS identified precise breakpoints, permitting confirmation by Sanger sequencing. WGS yielded identification of a de novo variant in a novel PCD gene TUBB4B. Here, WGS uplifted genetic diagnosis of PCD by identifying structural variants and novel modes of inheritance in new candidate genes. WGS could be an important component of the PCD diagnostic toolkit, increasing molecular diagnostic yield from current (70%) levels, and enhancing our understanding of fundamental biology of motile cilia and variants in the noncoding genome.

Loss of multi-level 3D genome organization during breast cancer progression.

Breast cancer entails intricate alterations in genome organization and expression. However, how three-dimensional (3D) chromatin structure changes in the progression from a normal to a breast cancer malignant state remains unknown. To address this, we conducted an analysis combining Hi-C data with lamina-associated domains (LADs), epigenomic marks, and gene expression in an in vitro model of breast cancer progression. Our results reveal that while the fundamental properties of topologically associating domains (TADs) are overall maintained, significant changes occur in the organization of compartments and subcompartments. These changes are closely correlated with alterations in the expression of oncogenic genes. We also observe a restructuring of TAD-TAD interactions, coinciding with a loss of spatial compartmentalization and radial positioning of the 3D genome. Notably, we identify a previously unrecognized interchromosomal insertion event, wherein a locus on chromosome 8 housing the MYC oncogene is inserted into a highly active subcompartment on chromosome 10. This insertion is accompanied by the formation of de novo enhancer contacts and activation of MYC , illustrating how structural genomic variants can alter the 3D genome to drive oncogenic states. In summary, our findings provide evidence for the loss of genome organization at multiple scales during breast cancer progression revealing novel relationships between genome 3D structure and oncogenic processes.

Canine hyper-sociability structural variants associated with altered three-dimensional chromatin state

Strong selection on complex traits can lead to skewed trait means and reduced trait variability in populations. An example of this phenomenon can be evidenced in allele frequency changes and skewed trait distributions driven by persistent human-directed selective pressures in domesticated species. Dog domestication is linked to several genomic variants; however, the functional impacts of these variants may not always be straightforward when found in non-coding regions of the genome. Four polymorphic transposable elements (TE) found within non-coding sites along a 5 Mb region on canine CFA6 have evolved due to directional selection associated with heightened human-directed hyper-sociability in domesticated dogs. We found that the polymorphic TE in intron 17 of the canine GTF2I gene, which was previously reported to be negatively correlated with canid human-directed hyper-sociability, is associated with altered chromatin looping and hence distinct cis-regulatory landscapes. We reported supporting evidence of an E2F1-DNA binding peak concordant with the altered loop and higher expression of GTF2I exon 18, indicative of alternative splicing. Globally, we discovered differences in pathways regulating the extra-cellular matrix with respect to TE copy number. Overall, we reported evidence suggesting an intriguing molecular convergence between the emergence of hypersocial behaviors in dogs and the same genes that, when hemizygous, produce human Williams Beuren Syndrome characterized by cranio-facial defects and heightened social behaviors. Our results additionally emphasize the often-overlooked potential role of chromatin architecture in social evolution.