Impacts of variation in the human genome on gene regulation

Enhancing cisplatin drug sensitivity through PARP3 inhibition: The influence on PDGF and G-coupled signal pathways in cancer

Drug resistance poses a significant challenge in cancer treatment despite the clinical efficacy of cisplatin. Identifying and targeting biomarkers open new ways to improve therapeutic outcomes. In this study, comprehensive bioinformatic analyses were employed, including a comparative analysis of multiple datasets, to evaluate overall survival and mutation hotspots in 27 base excision repair (BER) genes of more than 7,500 tumors across 23 cancer types. By using various parameters influencing patient survival, revealing that the overexpression of 15 distinct BER genes, particularly PARP3, NEIL3, and TDG, consistently correlated with poorer survival across multiple factors such as race, gender, and metastasis. Single nucleotide polymorphism (SNP) analyses within protein-coding regions highlighted the potential deleterious effects of mutations on protein structure and function. The investigation of mutation hotspots in BER proteins identified PARP3 due to its high mutation frequency. Moving from bioinformatics to wet lab experiments, cytotoxic experiments demonstrated that the absence of PARP3 by CRISPR/Cas9-mediated knockdown in MDA-MB-231 breast cancer cells increased drug activity towards cisplatin, carboplatin, and doxorubicin. Pathway analyses indicated the impact of PARP3 absence on the platelet-derived growth factor (PDGF) and G-coupled signal pathways on cisplatin exposure. PDGF, a critical regulator of various cellular functions, was downregulated in the absence of PARP3, suggesting a role in cancer progression. Moreover, the influence of PARP3 knockdown on G protein-coupled receptors (GPCRs) affects their function in the presence of cisplatin. In conclusion, the study demonstrated a synthetic lethal interaction between GPCRs, PDGF signaling pathways, and PARP3 gene silencing. PARP3 emerged as a promising target.

KRAS Promotes GLI2-Dependent Transcription during Pancreatic Carcinogenesis

Aberrant activation of GLI transcription factors has been implicated in the pathogenesis of different tumor types including pancreatic ductal adenocarcinoma. However, the mechanistic link with established drivers of this disease remains in part elusive. In this study, using a new genetically engineered mouse model overexpressing constitutively active mouse form of GLI2 and a combination of genome-wide assays, we provide evidence of a novel mechanism underlying the interplay between KRAS, a major driver of pancreatic ductal adenocarcinoma development, and GLI2 to control oncogenic gene expression. These mice, also expressing KrasG12D, show significantly reduced median survival rate and accelerated tumorigenesis compared with the KrasG12D only expressing mice. Analysis of the mechanism using RNA sequencing demonstrate higher levels of GLI2 targets, particularly tumor growth-promoting genes, including Ccnd1, N-Myc, and Bcl2, in KrasG12D mutant cells. Furthermore, chromatin immunoprecipitation sequencing studies showed that in these cells KrasG12D increases the levels of trimethylation of lysine 4 of the histone 3 (H3K4me3) at the promoter of GLI2 targets without affecting significantly the levels of other major active chromatin marks. Importantly, Gli2 knockdown reduces H3K4me3 enrichment and gene expression induced by mutant Kras. In summary, we demonstrate that Gli2 plays a significant role in pancreatic carcinogenesis by acting as a downstream effector of KrasG12D to control gene expression.

Characterization of the CsCENH3 protein and centromeric DNA profiles reveal the structures of centromeres in cucumber

Centromeres in eukaryotes mediate the accurate segregation of chromosomes during cell division. They serve as essential functional units of chromosomes and play a core role in the process of genome evolution. Centromeres are composed of satellite repeats and highly repetitive centromeric retrotransposons (CRs), which vary greatly even among closely related species. Cucumber (Cucumis sativus) is a globally cultivated and economically important vegetable and the only species in the Cucumis genus with seven pairs of chromosomes. Therefore, studying the centromeres of the Cucumis subgenus may yield valuable insights into its genome structure and evolution. Using chromatin immunoprecipitation (ChIP) techniques, we isolated centromeric DNA from cucumber reference line 9930. Our investigation into cucumber centromeres uncovered the centromeric satellite sequence, designated as CentCs, and the prevalence of Ty1/Copia long terminal repeat retrotransposons. In addition, active genes were identified in the CsCENH3 nucleosome regions with low transcription levels. To the best of our knowledge, this is the first time that characterization of centromeres has been achieved in cucumber. Meanwhile, our results on the distribution of CentCs and CsCRs in the subgenus Cucumis indicate that the content of centromeric repeats in the wild variants was significantly reduced compared with the cultivated cucumber. The results provide evidence for centromeric DNA amplification that occurred during the domestication process from wild to cultivated cucumber. Furthermore, these findings may offer new information for enhancing our understanding of phylogenetic relationships in the Cucumis genus.

Resf1 is a compound G4 quadruplex-associated tumor suppressor for triple negative breast cancer

Patients with ER-negative breast cancer have the worst prognosis of all breast cancer subtypes, often experiencing rapid recurrence or progression to metastatic disease shortly after diagnosis. Given that metastasis is the primary cause of mortality in most solid tumors, understanding metastatic biology is crucial for effective intervention. Using a mouse systems genetics approach, we previously identified 12 genes associated with metastatic susceptibility. Here, we extend those studies to identify Resf1, a poorly characterized gene, as a novel metastasis susceptibility gene in ER- breast cancer. Resf1 is a large, unstructured protein with an evolutionarily conserved intron-exon structure, but with poor amino acid conservation. CRISPR or gene trap mouse models crossed to the Polyoma Middle-T antigen genetically engineered mouse model (MMTV-PyMT) demonstrated that reduction of Resf1 resulted in a significant increase in tumor growth, a shortened overall survival time, and increased incidence and number of lung metastases, consistent with patient data. Furthermore, an analysis of matched tail and primary tissues revealed loss of the wildtype copy in tumor tissue, consistent with Resf1 being a tumor suppressor. Mechanistic analysis revealed a potential role of Resf1 in transcriptional control through association with compound G4 quadruplexes in expressed sequences, particularly those associated with ribosomal biogenesis. These results suggest that loss of Resf1 enhances tumor progression in ER- breast cancer through multiple alterations in both transcriptional and translational control.

PTCH1 Gene Variants, mRNA Expression, and Bioinformatics Insights in Mexican Cutaneous Squamous Cell Carcinoma Patients

BACKGROUND

Skin cancer is one of the most frequent types of cancer, and cutaneous squamous cell carcinoma (cSCC) constitutes 20% of non-melanoma skin cancer (NMSC) cases. PTCH1, a tumor suppressor gene involved in the Sonic hedgehog signaling pathway, plays a crucial role in neoplastic processes.

METHODS

An analytical cross-sectional study, encompassing 211 cSCC patients and 290 individuals in a control group (CG), was performed. A subgroup of samples was considered for the relative expression analysis, and the results were obtained using quantitative real-time PCR (qPCR) with TaqMan® probes. The functional, splicing, and disease-causing effects of the proposed variants were explored via bioinformatics.

RESULTS

cSCC was predominant in men, especially in sun-exposed areas such as the head and neck. No statistically significant differences were found regarding the rs357564, rs2236405, rs2297086, and rs41313327 variants of PTCH1, or in the risk of cSCC, nor in the mRNA expression between the cSCC group and CG. A functional effect of rs357564 and a disease-causing relation to rs41313327 was identified.

CONCLUSION

The proposed variants were not associated with cSCC risk in this Mexican population, but we recognize the need for analyzing larger population groups to elucidate the disease-causing role of rare variants.

PTCH1 gene variants rs357564, rs2236405, rs2297086 and rs41313327, mRNA and tissue expression in basal cell carcinoma patients from Western Mexico

BACKGROUND

Basal cell carcinoma (BCC) represents about 80% of all cases of skin cancer. The PTCH1 is a transmembrane protein of the Sonic Hedgehog signaling pathway that regulates cell proliferation. Genetic variants in PTCH1 gene have been previously described in association with BCC development. In addition, PTCH1 mRNA and protein expression analysis are also significant to understand its role in skin cancer physiopathology.

METHODS

An analytical cross-sectional study was performed, and a total of 250 BCC patients and 290 subjects from the control group (CG) were included, all born in western Mexico. The genotypes and relative expression of the mRNA were determined by TaqMan® assay. The protein expression was investigated in 70 BCC paraffin-embedded samples with PTCH1 antibodies. Semi-quantitative analysis was performed to determine the expression level in the immunostained cells.

RESULTS

We did not find evidence of an association between PTCH1 rs357564, rs2297086, rs2236405, and rs41313327 genetic variants and susceptibility to BCC. Likewise, no statistically significant differences were found in the comparison of the mRNA level expression between BCC and CG (p > 0.05). The PTCH1 protein showed a low expression in 6 of the analyzed samples and moderate expression in 1 sample. No association was found between genetic variants, protein expression, and demographic-clinical characteristics (p > 0.05).

CONCLUSION

The studied PTCH1 variants may not be associated with BCC development in the Western Mexico population. The PTCH1 mRNA levels were lower in patients with BCC compared to the control group, but its protein was underexpressed in the tissue samples.

Exploring quantitative traits-associated copy number deletions through reanalysis of UK10K consortium whole genome sequencing cohorts

OBJECTIVES

We performed comprehensive association analyses of common high-confidence gnomAD-reported copy number deletions (CNDs) with 60 quantitative traits from UK10K consortium WGS data.

METHODS

The study made use of data generated by the UK10K Consortium. UK10K consortium WGS data consist of TwinsUK (n = 1754, middle-aged females) and ALSPAC (n = 1867, birth to adolescence) cohorts. UK10K consortium called 18,739 CNDs (hg19) with GenomeSTRiP software. After filtering out variants with minor allele frequency < 0.05 or HWE P < 1.0 × 10- 6, 1222 (TwinsUK) and 1211 (ALSPAC) CNDs remained for association analyses with 60 normalized quantitative traits.

RESULTS

We identified 23 genome-wide significant associations at 13 loci, among which 2 associations reached experiment-wide significance. We found that two common deletions in chromosome 4, located between WDR1 and ZNF518B (23.3 kb, dbVar ID:nssv15888957, 4:10211262-10,234,569 and 9.8 kb, dbVar ID:nssv15888975, 4:10392422-10,402,191), were associated with uric acid levels (P = 5.23 × 10- 11 and 2.29 × 10- 8, respectively). We also discovered a novel deletion spanning chromosome 18 (823 bp, dbVar ID: nssv15841628, 8:74347187-74,348,010) associated with low HDL cholesterol levels (P = 4.15 × 10- 7). Additionally, we observed two red blood cell traits-associated loci with genome-wide significance, a 13.2 kb deletion in 7q22.1 (nssv15922542) and a 3.7 kb deletion in 12q24.12 (nssv15813226), both of which were located in regions previously reported to be associated with red blood cell traits. Two deletions in 11q11 (nssv15803200 and nssv15802240), where clusters of multiple olfactory receptor genes exist, and a deletion (nssv15929560) upstream to DOCK5 were associated with childhood obesity. Finally, when defining Trait-Associated copy number Deletions (TADs) as CNDs with phenotype associations at sub-threshold significance (P < 10- 3), we identified 157 (97.5%) out of 161 TADs in non-coding regions, with a mean size of 4 kb (range: 209 - 47,942 bp).

CONCLUSION

We conducted a reanalysis of the UK10K Whole Genome Sequencing cohort, which led to the identification of multiple high confidence copy number deletions associated with quantitative traits. These deletions have standard dbVar IDs and replicate previous findings, as well as reveal novel loci that require further replication studies.

Comprehensive detection of structural variation and transposable element differences between wild type laboratory lineages of C. elegans

Genomic structural variations (SVs) and transposable elements (TEs) can be significant contributors to genome evolution, altered gene expression, and risk of genetic diseases. Recent advancements in long-read sequencing have greatly improved the quality of de novo genome assemblies and enhanced the detection of sequence variants at the scale of hundreds or thousands of bases. Comparisons between two diverged wild isolates of Caenorhabditis elegans, the Bristol and Hawaiian strains, have been widely utilized in the analysis of small genetic variations. Genetic drift, including SVs and rearrangements of repeated sequences such as TEs, can occur over time from long-term maintenance of wild type isolates within the laboratory. To comprehensively detect both large and small structural variations as well as TEs due to genetic drift, we generated de novo genome assemblies and annotations for each strain from our lab collection using both long- and short-read sequencing and compared our assemblies and annotations with that of other lab wild type strains. Within our lab assemblies, we annotate over 3.1Mb of sequence divergence between the Bristol and Hawaiian isolates: 337,584 SNPs, 94,503 small insertion-deletions (<50bp), and 4,334 structural variations (>50bp). Further, we define the location and movement of specific DNA TEs between N2 Bristol and CB4856 Hawaiian wild type isolates. Specifically, we find the N2 Bristol genome has 20.6% more TEs from the Tc1/mariner family than the CB4856 Hawaiian genome. Moreover, we identified Zator elements as the most abundant and mobile TE family in the genome. Using specific TE sequences with unique SNPs, we also identify 38 TEs that moved intrachromosomally and 9 TEs that moved interchromosomally between the N2 Bristol and CB4856 Hawaiian genomes. By comparing the de novo genome assembly of our lab collection Bristol isolate to the VC2010 Bristol assembly, we also reveal that lab lineages display over 2 Mb of total variation: 1,162 SNPs, 1,528 indels, and 897 SVs with 95% of the variation due to SVs. Overall, our work demonstrates the unique contribution of SVs and TEs to variation and genetic drift between wild type laboratory strains assumed to be isogenic despite growing evidence of genetic drift and phenotypic variation.

Novel GALT variations and genetic spectrum in Turkish population with the correlation of genotype and phenotype

Classic galactosemia (OMIM#230400) is an autosomal recessive inborn error of carbohydrate metabolism caused by a deficiency of the galactose-1-phosphate-uridyl-transferase enzyme encoded by the GALT gene. Even though a galactose-restricted diet efficiently resolves the acute complications, it is insufficient to prevent long-term complications regarding speech defects, intellectual functioning, premature ovarian failure, cataract, hepatomegaly, dysarthria, ataxia, and tremor. Seventy-seven patients who were genetically diagnosed with classic galactosemia were included in this cohort. Identified novel variants were classified based on their predicted effect on the GALT function. Further, potential genotype-phenotype correlations were investigated via statistical analysis. In total, 18 different sequence variants were identified, including four novels (c.200delG/p.(Arg67Profs* 19), c.533T>G/ p.(Met178Arg), c.708_709delGT/p.(Ser236Argfs* 30), c.467C>A/p.(Ser156* )). Jaundice was the most common short-term finding with 80% (61/77). Even with early diagnosis, intellectual disability is encountered with 36% (27/74) of the long-term complications. Patients with biallelic missense variants have a significantly higher prevalence of cataracts (OR: 17.9). Longitudinal observations showed attenuation of cataracts and hepatomegaly. This study has shown the GALT variation spectrum of the Turkish population with a 30-year retrospective cohort, submitting a significant contribution to the genotype/phenotype correlation in galactosemia. This study also highlights the cost-effective importance of Sanger sequencing in the diagnosis of single-gene metabolic diseases.

Integrative analyses of RNA-seq and ChIP-seq Reveal MITF as a Target Gene of TFPI-2 in MDA231 Cells

Breast cancer is the most prevalent cancer in female patients worldwide. Tissue factor pathway inhibitor 2 (TFPI-2) is identified as an important tumor suppressor in various cancers. Recent studies have shown that TFPI-2 translocates into the nucleus, where it modulates the transcription of the matrix metalloproteinase-2 (MMP-2) gene. However, its biological role and molecular mechanisms in the progression of breast cancer remain unclear. In this study, we identified 5125 differentially expressed genes (DEGs) from RNA sequencing (RNA-seq) in TFPI-2-overexpressing MDA231 cells compared with control cells. Gene ontology and Kyoto encyclopedia of genes and genomes (KEGG) analysis shown that cell cycle, cell differentiation, proteoglycans in cancer, and pathways associated with cancer were highly enriched in downregulated DEGs. Integration of the RNA-seq and ChIP-sequencing (ChIP-seq) data identified 73 genes directly controlled by TFPI-2 in MDA231 cells. Among them, melanocyte inducing transcription factor (MITF) gene expression was repressed by TFPI-2, which was further verified by a luciferase reporter assay and ChIP-quantitative PCR. Our study provides evidence of a novel role of TFPI-2 in human breast cancer involving targeting of the MITF.

De novo assembly and annotation of the singing mouse genome

BACKGROUND

Developing genomic resources for a diverse range of species is an important step towards understanding the mechanisms underlying complex traits. Specifically, organisms that exhibit unique and accessible phenotypes-of-interest allow researchers to address questions that may be ill-suited to traditional model organisms. We sequenced the genome and transcriptome of Alston's singing mouse (Scotinomys teguina), an emerging model for social cognition and vocal communication. In addition to producing advertisement songs used for mate attraction and male-male competition, these rodents are diurnal, live at high-altitudes, and are obligate insectivores, providing opportunities to explore diverse physiological, ecological, and evolutionary questions.

RESULTS

Using PromethION, Illumina, and PacBio sequencing, we produced an annotated genome and transcriptome, which were validated using gene expression and functional enrichment analyses. To assess the usefulness of our assemblies, we performed single nuclei sequencing on cells of the orofacial motor cortex, a brain region implicated in song coordination, identifying 12 cell types.

CONCLUSIONS

These resources will provide the opportunity to identify the molecular basis of complex traits in singing mice as well as to contribute data that can be used for large-scale comparative analyses.

Considerations for reproducible omics in aging research

Technical advancements over the past two decades have enabled the measurement of the panoply of molecules of cells and tissues including transcriptomes, epigenomes, metabolomes and proteomes at unprecedented resolution. Unbiased profiling of these molecular landscapes in the context of aging can reveal important details about mechanisms underlying age-related functional decline and age-related diseases. However, the high-throughput nature of these experiments creates unique analytical and design demands for robustness and reproducibility. In addition, 'omic' experiments are generally onerous, making it crucial to effectively design them to eliminate as many spurious sources of variation as possible as well as account for any biological or technical parameter that may influence such measures. In this Perspective, we provide general guidelines on best practices in the design and analysis of omic experiments in aging research from experimental design to data analysis and considerations for long-term reproducibility and validation of such studies.

Pharmacogenetic impact of SLC22A1 gene variant rs628031 (G/A) in newly diagnosed Indian type 2 diabetes patients undergoing metformin monotherapy

OBJECTIVES

Type 2 diabetes (T2D) imposes an enormous burden all over the world in both developed and developing countries. Inter-individual differences are attributed to polymorphisms in candidate genes resulting in altered absorption, transportation, distribution, and metabolism of oral antidiabetic drugs (OADs). Hence, the present study was undertaken to evaluate the pharmacogenetic impact of SLC22A1 gene variant rs628031 (G/A) on metformin monotherapy in newly diagnosed untreated T2D patients.

METHODS

Newly diagnosed T2D patients ( n  = 500) were enrolled according to inclusion/exclusion criteria. Initially, enrolled subjects were prescribed metformin monotherapy and followed up for at least 12 weeks. Response to metformin was evaluated in 478 patients who revisited for follow-up by measuring HbA1c.

RESULT

Out of 478 patients, 373 were responders to metformin monotherapy while 105 were non-responders. The pharmacogenetic impact was evaluated by genotype, haplotype, and pharmacogenetic analyses. 'GG' genotype and 'G' allele of SLC22A1 rs628031 G/A were observed in 48.8% and 67.7% of Met responders, respectively, while 20.9% and 49.1 % were in non-responders. Therefore, there was a 2.18-fold increase in the success rate of Met therapeutics.

CONCLUSION

Individuals carrying the 'GG' genotype or 'G' allele for SLC22A1 gene variant rs628031 G/A are better responders for Metformin monotherapy.

Goat MyoD1: mRNA expression, InDel and CNV detection and their associations with growth traits

The Myogenic differentiation 1 (MyoD1) gene is a crucial regulator of muscle formation and differentiation. However, there are few studies on the mRNA expression pattern of the goat MyoD1 gene and its effect on goat growth and development. To address this, we investigated the mRNA expression of the MyoD1 gene in several tissues of fetal and adult goats, containing heart, liver, spleen, lung, kidney and skeletal muscle. The results focused on the expression of the MyoD1 gene in skeletal muscle of fetal goats was much higher than adult goats, suggesting its important role in skeletal muscle formation and development. Following, a total of 619 Shaanbei White Cashmere goats (SBWCs) were used to monitor the InDel (Insertion/Deletion) and CNV (Copy Number Variation) variations of the MyoD1 gene. Three InDel loci were identified, and there was no significant correlation with goat growth traits. Furthermore, a CNV locus containing the MyoD1 gene exon with three types (Loss type, Normal type, Gain type) were identified. The association analysis results showed that the CNV locus was significantly associated with body weight, height at hip cross, heart girth and hip width in SBWCs (P < 0.05). Meanwhile, the Gain type of CNV exhibited the best growth traits and good consistency among three types in goats, suggesting its potential as a DNA marker for marker-assisted breeding of goats. Overall, our study provided a scientific basis for breeding goats with better growth and development traits.

Radiomics Approaches for the Prediction of Pathological Complete Response after Neoadjuvant Treatment in Locally Advanced Rectal Cancer: Ready for Prime Time?

In recent years, neoadjuvant therapy of locally advanced rectal cancer has seen tremendous modifications. Adding neoadjuvant chemotherapy before or after chemoradiotherapy significantly increases loco-regional disease-free survival, negative surgical margin rates, and complete response rates. The higher complete rate is particularly clinically meaningful given the possibility of organ preservation in this specific sub-population, without compromising overall survival. However, all locally advanced rectal cancer most likely does not benefit from total neoadjuvant therapy (TNT), but experiences higher toxicity rates. Diagnosis of complete response after neoadjuvant therapy is a real challenge, with a risk of false negatives and possible under-treatment. These new therapeutic approaches thus raise the need for better selection tools, enabling a personalized therapeutic approach for each patient. These tools mostly focus on the prediction of the pathological complete response given the clinical impact. In this article, we review the place of different biomarkers (clinical, biological, genomics, transcriptomics, proteomics, and radiomics) as well as their clinical implementation and discuss the most recent trends for future steps in prediction modeling in patients with locally advanced rectal cancer.

Pan-cancer analysis identifies DDX56 as a prognostic biomarker associated with immune infiltration and drug sensitivity

DDX56, a member of the RNA helicase family, is upregulated in colon adenocarcinoma, lung squamous cell carcinoma, and osteosarcoma. However, the relationships between DDX56 and other tumors are not clear, and the molecular mechanism of its action is not fully understood. Here, we explore the biological functions of DDX56 in 31 solid tumors and clarify that DDX56 can promote oncogenesis and progression in multiple tumor types based on multi-omics data. Bioinformatics analysis revealed that the cancer-promoting effects of DDX56 were achieved by facilitating tumor cell proliferation, inhibiting apoptosis, inducing drug resistance, and influencing immune cell infiltration. Furthermore, we found that copy number alterations and low DNA methylation of DDX56 were likely to be related to aberrantly high DDX56 expression. Our results suggest that DDX56 is a potential pan-cancer biomarker that could be used to predict survival and response to therapy, as well as a potential novel therapeutic target. We validated some of our results and illustrated their reliability using CRISPR Screens data. In conclusion, our results clarify the role of DDX56 in the occurrence and development of multiple cancers and provide insight into the molecular mechanisms involved in the process of pathogenesis, indicating a direction for future research on DDX56 in cancers.

Computational approaches for predicting variant impact: An overview from resources, principles to applications

One objective of human genetics is to unveil the variants that contribute to human diseases. With the rapid development and wide use of next-generation sequencing (NGS), massive genomic sequence data have been created, making personal genetic information available. Conventional experimental evidence is critical in establishing the relationship between sequence variants and phenotype but with low efficiency. Due to the lack of comprehensive databases and resources which present clinical and experimental evidence on genotype-phenotype relationship, as well as accumulating variants found from NGS, different computational tools that can predict the impact of the variants on phenotype have been greatly developed to bridge the gap. In this review, we present a brief introduction and discussion about the computational approaches for variant impact prediction. Following an innovative manner, we mainly focus on approaches for non-synonymous variants (nsSNVs) impact prediction and categorize them into six classes. Their underlying rationale and constraints, together with the concerns and remedies raised from comparative studies are discussed. We also present how the predictive approaches employed in different research. Although diverse constraints exist, the computational predictive approaches are indispensable in exploring genotype-phenotype relationship.

Detection of InDel and CNV of SPAG17 gene and their associations with bovine growth traits

Sperm-associated antigen 17 (SPAG17) gene encodes a central pair protein, which is involved in flagellar motility, male fertility and skeletal growth in ruminants. The insertions/deletions (indels) and copy number variations (CNVs) influence phenotypic traits by altering the sequences and copy numbers of functional genes, respectively. This study identified a novel 8-bp indel of SPAG17 gene in 1520 individuals from eight different cattle breeds, as well as a novel CNV region in 355 animals. The correlation analysis of indel showed that the individuals of ID genotype had superior performance traits such as body height (p = 0.038) and body slanting length (p = 0.041) as compared to other genotypes in Xianan cattle. For the CNV, different copy numbers were closely related to the body height in Qinchuan (p = 0.045) and body weight in Xianan (p = 0.036) breeds. Importantly, significant difference was observed between the 8-bp indel and the copy number loss in Xianan breed (p < 0.01). These findings indicated that the variations within the bovine SPAG17 gene can be considered as an effective DNA molecular marker for beef cattle breeding.

Network Approaches for Charting the Transcriptomic and Epigenetic Landscape of the Developmental Origins of Health and Disease

The early developmental phase is of critical importance for human health and disease later in life. To decipher the molecular mechanisms at play, current biomedical research is increasingly relying on large quantities of diverse omics data. The integration and interpretation of the different datasets pose a critical challenge towards the holistic understanding of the complex biological processes that are involved in early development. In this review, we outline the major transcriptomic and epigenetic processes and the respective datasets that are most relevant for studying the periconceptional period. We cover both basic data processing and analysis steps, as well as more advanced data integration methods. A particular focus is given to network-based methods. Finally, we review the medical applications of such integrative analyses.

Population features of alleles and genotypes frequency distribution of polymorphic genetic markers of antipsychotic medications pharmacokinetics in the Kazakh population

The presented article is relevant, as the main goals of schizophrenia treatment are to achieve a response to psychopharmacotherapy, reduction and stabilization of psychopathological symptoms, qualitative remission, which in general implies the creation of a stable quality of life for the patient. The purpose of the study was to evaluate the population features of the frequency distribution of alleles and genotypes of polymorphic genetic variants of according to genome-wide association studies analysis of pharmacokinetics-associated antipsychotic medications, in an ethnically homogeneous Kazakh population. The research material was deoxyribonucleic acid (DNA) isolated from the peripheral blood of 1,800 conditionally healthy persons of Kazakh nationality. DNA isolation was carried out by the magnetic polyvinyl alcohol magnetic particle separation method. The analysis of the frequency distribution of the studied genotypes in the Kazakh population showed their compliance with the Hardy-Weinberg equilibrium for all studied polymorphisms (p > .05). The obtained results showed that CYP2C19 (rs4244285, rs4986893) polymorphisms occurs in Kazakhs significantly more often than European and a number of Asian populations, which significantly affects the decrease in effectiveness and increases the risk of side complications during therapy with antipsychotic medications in the Kazakh population.

Exploring Genomic Variations in Nematode-Resistant Mutant Rice Lines

Rice (Oryza sativa) production is seriously affected by the root-knot nematode Meloidogyne graminicola, which has emerged as a menace in upland and irrigated rice cultivation systems. Previously, activation tagging in rice was utilized to identify candidate gene(s) conferring resistance against M. graminicola. T-DNA insertional mutants were developed in a rice landrace (acc. JBT 36/14), and four mutant lines showed nematode resistance. Whole-genome sequencing of JBT 36/14 was done along with the four nematode resistance mutant lines to identify the structural genetic variations that might be contributing to M. graminicola resistance. Sequencing on Illumina NovaSeq 6000 platform identified 482,234 genetic variations in JBT 36/14 including 448,989 SNPs and 33,245 InDels compared to reference indica genome. In addition, 293,238-553,648 unique SNPs and 32,395-65,572 unique InDels were found in the four mutant lines compared to their JBT 36/14 background, of which 93,224 SNPs and 8,170 InDels were common between all the mutant lines. Functional annotation of genes containing these structural variations showed that the majority of them were involved in metabolism and growth. Trait analysis revealed that most of these genes were involved in morphological traits, physiological traits and stress resistance. Additionally, several families of transcription factors, such as FAR1, bHLH, and NAC, and putative susceptibility (S) genes, showed the presence of SNPs and InDels. Our results indicate that subject to further genetic validations, these structural genetic variations may be involved in conferring nematode resistance to the rice mutant lines.

Machine learning for multi-omics data integration in cancer

Multi-omics data analysis is an important aspect of cancer molecular biology studies and has led to ground-breaking discoveries. Many efforts have been made to develop machine learning methods that automatically integrate omics data. Here, we review machine learning tools categorized as either general-purpose or task-specific, covering both supervised and unsupervised learning for integrative analysis of multi-omics data. We benchmark the performance of five machine learning approaches using data from the Cancer Cell Line Encyclopedia, reporting accuracy on cancer type classification and mean absolute error on drug response prediction, and evaluating runtime efficiency. This review provides recommendations to researchers regarding suitable machine learning method selection for their specific applications. It should also promote the development of novel machine learning methodologies for data integration, which will be essential for drug discovery, clinical trial design, and personalized treatments.

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Featuring a balance of both biological and technical content

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Categorizing the reviewed tools into general purpose and task-specific

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Performing an independent benchmarking analysis using a publicly available dataset

A novel complex genomic rearrangement affecting the KCNJ2 regulatory region causes a variant of Cooks syndrome

Cooks syndrome (CS) is an ultrarare limb malformation due to in tandem microduplications involving KCNJ2 and extending to the 5' regulatory element of SOX9. To date, six CS families were resolved at the molecular level. Subsequent studies explored the evolutionary and pathological complexities of the SOX9-KCNJ2/Sox9-Kcnj2 locus, and suggested a key role for the formation of novel topologically associating domain (TAD) by inter-TAD duplications in causing CS. Here, we report a unique case of CS associated with a de novo 1;17 translocation affecting the KCNJ2 locus. On chromosome 17, the breakpoint mapped between KCNJ16 and KCNJ2, and combined with a ~ 5 kb deletion in the 5' of KCNJ2. Based on available capture Hi-C data, the breakpoint on chromosome 17 separated KCNJ2 from a putative enhancer. Gene expression analysis demonstrated downregulation of KCNJ2 in both patient's blood cells and cultured skin fibroblasts. Our findings suggest that a complex rearrangement falling in the 5' of KCNJ2 may mimic the developmental consequences of in tandem duplications affecting the SOX9-KCNJ2/Sox9-Kcnj2 locus. This finding adds weight to the notion of an intricate role of gene regulatory regions and, presumably, the related three-dimensional chromatin structure in normal and abnormal human morphology.

Epigenetic readers and lung cancer: the rs2427964C>T variant of the bromodomain and extraterminal domain gene BRD3 is associated with poorer survival outcome in NSCLC

Bromodomain and extraterminal domain (BET) proteins are epigenetic readers that regulate gene expression. We investigated whether variants in BET genes are associated with survival outcomes for lung cancer. To do this, the associations between 77 variants in BET family genes and survival outcomes were analyzed in 773 non‐small‐cell lung cancer (NSCLC) patients who underwent surgery (349 and 424 patients in the discovery and validation cohorts, respectively). We found that six variants were significantly associated with overall survival (OS) in the discovery cohort, and one variant (rs2506711C>T) was replicated in the validation cohort. BRD3 rs2506711C>T is located in the repressed area and has a strong linkage disequilibrium with rs2427964C>T in the promoter region. BRD3 rs2427964C>T was significantly associated with worse OS in the discovery cohort, validation cohort, and combined analysis. In a luciferase assay, promoter activity in the BRD3 rs2427964 T allele was significantly higher than that in the BRD3 rs2427964 C allele, which selectively bound with the transcriptional repressor SIN3A. Knockdown of BRD3 with BRD3‐specific siRNA decreased the proliferation and migration of lung cancer cells while also increasing the rate of apoptosis. These results suggest that BRD3 rs2427964C>T increases BRD3 expression through increased promoter activity, which is associated with poor prognosis for lung cancer.

Gut Microbial SNPs Induced by High-Fiber Diet Dominate Nutrition Metabolism and Environmental Adaption of Faecalibacterium prausnitzii in Obese Children

Dietary intervention is effective in human health promotion through modulation of gut microbiota. Diet can cause single-nucleotide polymorphisms (SNPs) to occur in the gut microbiota, and some of these variations may lead to functional changes in human health. In this study, we performed a systematic SNP analysis based on metagenomic data collected from children with Prader–Willi syndrome (PWS, n = 17) and simple obese (SO) children (n = 19), who had better healthy conditions after receiving high-fiber diet intervention. We found that the intervention increased the SNP proportions of Faecalibacterium, Bifidobacterium, and Clostridium and decreased those of Bacteroides in all children. Besides, the PWS children had Collinsella increased and Ruminococcus decreased, whereas the SO had Blautia and Escherichia decreased. There were much more BiasSNPs in PWS than in SO (4,465 vs 303), and only 81 of them appeared in both groups, of which 78 were from Faecalibacterium prausnitzii, and 51 were nonsynonymous mutations. These nonsynonymous variations were mainly related to pathways of environmental adaptation and nutrition metabolism, particularly to carbohydrate and nucleotide metabolism. In addition, dominant strains carrying BiasSNPs in all children shifted from F. prausnitzii AF32-8AC and F. prausnitzii 942/30-2 to F. prausnitzii SSTS Bg7063 and F. prausnitzii JG BgPS064 after the dietary intervention. Furthermore, although the abundance of Bifidobacterium increased significantly by the intervention and became dominant strains responsible for nutrition metabolism, they had less BiasSNPs between the pre- and post-intervention group in comparison with Faecalibacterium. The finding of F. prausnitzii as important functional strains influenced by the intervention highlights the superiority of applying SNP analysis in studies of gut microbiota. This study provided evidence and support for the effect of dietary intervention on gut microbial SNPs, and gave some enlightenments for disease treatment.

Cutaneous Melanoma Classification: The Importance of High-Throughput Genomic Technologies

Cutaneous melanoma is an aggressive tumor responsible for 90% of mortality related to skin cancer. In the recent years, the discovery of driving mutations in melanoma has led to better treatment approaches. The last decade has seen a genomic revolution in the field of cancer. Such genomic revolution has led to the production of an unprecedented mole of data. High-throughput genomic technologies have facilitated the genomic, transcriptomic and epigenomic profiling of several cancers, including melanoma. Nevertheless, there are a number of newer genomic technologies that have not yet been employed in large studies. In this article we describe the current classification of cutaneous melanoma, we review the current knowledge of the main genetic alterations of cutaneous melanoma and their related impact on targeted therapies, and we describe the most recent high-throughput genomic technologies, highlighting their advantages and disadvantages. We hope that the current review will also help scientists to identify the most suitable technology to address melanoma-related relevant questions. The translation of this knowledge and all actual advancements into the clinical practice will be helpful in better defining the different molecular subsets of melanoma patients and provide new tools to address relevant questions on disease management. Genomic technologies might indeed allow to better predict the biological - and, subsequently, clinical - behavior for each subset of melanoma patients as well as to even identify all molecular changes in tumor cell populations during disease evolution toward a real achievement of a personalized medicine.

Analysis and Interpretation of the Impact of Missense Variants in Cancer

Large scale genome sequencing allowed the identification of a massive number of genetic variations, whose impact on human health is still unknown. In this review we analyze, by an in silico-based strategy, the impact of missense variants on cancer-related genes, whose effect on protein stability and function was experimentally determined. We collected a set of 164 variants from 11 proteins to analyze the impact of missense mutations at structural and functional levels, and to assess the performance of state-of-the-art methods (FoldX and Meta-SNP) for predicting protein stability change and pathogenicity. The result of our analysis shows that a combination of experimental data on protein stability and in silico pathogenicity predictions allowed the identification of a subset of variants with a high probability of having a deleterious phenotypic effect, as confirmed by the significant enrichment of the subset in variants annotated in the COSMIC database as putative cancer-driving variants. Our analysis suggests that the integration of experimental and computational approaches may contribute to evaluate the risk for complex disorders and develop more effective treatment strategies.

Prime editing in mice reveals the essentiality of a single base in driving tissue-specific gene expression

BACKGROUND

Most single nucleotide variants (SNVs) occur in noncoding sequence where millions of transcription factor binding sites (TFBS) reside. Here, a comparative analysis of CRISPR-mediated homology-directed repair (HDR) versus the recently reported prime editing 2 (PE2) system was carried out in mice over a TFBS called a CArG box in the Tspan2 promoter.

RESULTS

Quantitative RT-PCR showed loss of Tspan2 mRNA in aorta and bladder, but not heart or brain, of mice homozygous for an HDR-mediated three base pair substitution in the Tspan2 CArG box. Using the same protospacer, mice homozygous for a PE2-mediated single-base substitution in the Tspan2 CArG box displayed similar cell-specific loss of Tspan2 mRNA; expression of an overlapping long noncoding RNA was also nearly abolished in aorta and bladder. Immuno-RNA fluorescence in situ hybridization validated loss of Tspan2 in vascular smooth muscle cells of HDR and PE2 CArG box mutant mice. Targeted sequencing demonstrated variable frequencies of on-target editing in all PE2 and HDR founders. However, whereas no on-target indels were detected in any of the PE2 founders, all HDR founders showed varying levels of on-target indels. Off-target analysis by targeted sequencing revealed mutations in many HDR founders, but none in PE2 founders.

CONCLUSIONS

PE2 directs high-fidelity editing of a single base in a TFBS leading to cell-specific loss in expression of an mRNA/long noncoding RNA gene pair. The PE2 platform expands the genome editing toolbox for modeling and correcting relevant noncoding SNVs in the mouse.

Imprints of selection in peripheral and ecologically marginal central-eastern European Scots pine populations

Knowledge of the molecular mechanisms underlying the stress response in plants is essential to understand evolutionary processes that result in long-term persistence of populations. Populations inhabiting marginal ecological conditions at the distribution range periphery may have preserved imprints of natural selection that have shaped functional genetic variation of the species. Our aim was to evaluate the extent of selection processes in the extremely fragmented, peripheral and isolated populations of Scots pine in central-eastern Europe. Autochthonous populations of the Carpathian Mts. and the Pannonian Basin were sampled and drought stress-related candidate genes were re-sequenced. Neutrality tests and outlier detection approaches were applied to infer the effect and direction of selection. Populations retained high genetic diversity by preserving a high number of alleles and haplotypes, many of them being population specific. Neutrality tests and outlier detection highlighted nucleotide positions that are under divergent selection and may be involved in local adaptation. The detected genetic pattern confirms that natural selection has played an important role in shaping modern-day genetic variation in marginal Scots pine populations, allowing for the long-term persistence of populations. Selection detected at functional regions possibly acts to maintain diversity and counteract the effect of genetic erosion.

RMVar: an updated database of functional variants involved in RNA modifications

Distinguishing the few disease-related variants from a massive number of passenger variants is a major challenge. Variants affecting RNA modifications that play critical roles in many aspects of RNA metabolism have recently been linked to many human diseases, such as cancers. Evaluating the effect of genetic variants on RNA modifications will provide a new perspective for understanding the pathogenic mechanism of human diseases. Previously, we developed a database called 'm6AVar' to host variants associated with m6A, one of the most prevalent RNA modifications in eukaryotes. To host all RNA modification (RM)-associated variants, here we present an updated version of m6AVar renamed RMVar (http://rmvar.renlab.org). In this update, RMVar contains 1 678 126 RM-associated variants for 9 kinds of RNA modifications, namely m6A, m6Am, m1A, pseudouridine, m5C, m5U, 2'-O-Me, A-to-I and m7G, at three confidence levels. Moreover, RBP binding regions, miRNA targets, splicing events and circRNAs were integrated to assist investigations of the effects of RM-associated variants on posttranscriptional regulation. In addition, disease-related information was integrated from ClinVar and other genome-wide association studies (GWAS) to investigate the relationship between RM-associated variants and diseases. We expect that RMVar may boost further functional studies on genetic variants affecting RNA modifications.

Combination of Genome-Wide Polymorphisms and Copy Number Variations of Pharmacogenes in Koreans

For predicting phenotypes and executing precision medicine, combination analysis of single nucleotide variants (SNVs) genotyping with copy number variations (CNVs) is required. The aim of this study was to discover SNVs or common copy CNVs and examine the combined frequencies of SNVs and CNVs in pharmacogenes using the Korean genome and epidemiology study (KoGES), a consortium project. The genotypes (N = 72,299) and CNV data (N = 1000) were provided by the Korean National Institute of Health, Korea Centers for Disease Control and Prevention. The allele frequencies of SNVs, CNVs, and combined SNVs with CNVs were calculated and haplotype analysis was performed. CYP2D6 rs1065852 (c.100C>T, p.P34S) was the most common variant allele (48.23%). A total of 8454 haplotype blocks in 18 pharmacogenes were estimated. DMD ranked the highest in frequency for gene gain (64.52%), while TPMT ranked the highest in frequency for gene loss (51.80%). Copy number gain of CYP4F2 was observed in 22 subjects; 13 of those subjects were carriers with CYP4F2*3 gain. In the case of TPMT, approximately one-half of the participants (N = 308) had loss of the TPMT*1*1 diplotype. The frequencies of SNVs and CNVs in pharmacogenes were determined using the Korean cohort-based genome-wide association study.

Identification of primary copy number variations reveal enrichment of Calcium, and MAPK pathways sensitizing secondary sites for autism

Background

Autism is a neurodevelopmental condition with genetic heterogeneity. It is characterized by difficulties in reciprocal social interactions with strong repetitive behaviors and stereotyped interests. Copy number variations (CNVs) are genomic structural variations altering the genomic structure either by duplication or deletion. De novo or inherited CNVs are found in 5–10% of autistic subjects with a size range of few kilobases to several megabases. CNVs predispose humans to various diseases by altering gene regulation, generation of chimeric genes, and disruption of the coding region or through position effect. Although, CNVs are not the initiating event in pathogenesis; additional preceding mutations might be essential for disease manifestation. The present study is aimed to identify the primary CNVs responsible for autism susceptibility in healthy cohorts to sensitize secondary-hits. In the current investigation, primary-hit autism gene CNVs are characterized in 1715 healthy cohorts of varying ethnicities across 12 populations using Affymetrix high-resolution array study. Thirty-eight individuals from twelve families residing in Karnataka, India, with the age group of 13–73 years are included for the comparative CNV analysis. The findings are validated against global 179 autism whole-exome sequence datasets derived from Simons Simplex Collection. These datasets are deposited at the Simons Foundation Autism Research Initiative (SFARI) database.

Results

The study revealed that 34.8% of the subjects carried 2% primary-hit CNV burden with 73 singleton-autism genes in different clusters. Of these, three conserved CNV breakpoints were identified with ARHGAP11B, DUSP22, and CHRNA7 as the target genes across 12 populations. Enrichment analysis of the population-specific autism genes revealed two signaling pathways—calcium and mitogen-activated protein kinases (MAPK) in the CNV identified regions. These impaired pathways affected the downstream cascades of neuronal function and physiology, leading to autism behavior. The pathway analysis of enriched genes unravelled complex protein interaction networks, which sensitized secondary sites for autism. Further, the identification of miRNA targets associated with autism gene CNVs added severity to the condition.

Conclusion

These findings contribute to an atlas of primary-hit genes to detect autism susceptibility in healthy cohorts, indicating their impact on secondary sites for manifestation.

Role of m6A RNA methylation in cardiovascular disease (Review)

N⁶-methyladenosine (m⁶A) is the most prevalent and abundant type of internal post-transcriptional RNA modification in eukaryotic cells. Multiple types of RNA, including mRNAs, rRNAs, tRNAs, long non-coding RNAs and microRNAs, are involved in m⁶A methylation. The biological function of m⁶A modification is dynamically and reversibly mediated by methyltransferases (writers), demethylases (erasers) and m⁶A binding proteins (readers). The methyltransferase complex is responsible for the catalyzation of m⁶A modification and is typically made up of methyltransferase-like (METTL)3, METTL14 and Wilms tumor 1-associated protein. Erasers remove methylation by fat mass and obesity-associated protein and ALKB homolog 5. Readers play a role through the recognition of m⁶A-modified targeted RNA. The YT521-B homology domain family, heterogeneous nuclear ribonucleoprotein and insulin-like growth factor 2 mRNA-binding protein serve as m⁶A readers. The m⁶A methylation on transcripts plays a pivotal role in the regulation of downstream molecular events and biological functions, such as RNA splicing, transport, stability and translatability at the post-transcriptional level. The dysregulation of m⁶A modification is associated with cancer, drug resistance, virus replication and the pluripotency of embryonic stem cells. Recently, a number of studies have identified aberrant m⁶A methylation in cardiovascular diseases (CVDs), including cardiac hypertrophy, heart failure, arterial aneurysm, vascular calcification and pulmonary hypertension. The aim of the present review article was to summarize the recent research progress on the role of m⁶A modification in CVD and give a brief perspective on its prospective applications in CVD.

The Role of Micro-RNAs and Circulating Tumor Markers as Predictors of Response to Neoadjuvant Therapy in Locally Advanced Rectal Cancer

The response to neoadjuvant chemoradiation (nCRT) is a critical step in the management of locally advanced rectal cancer (LARC) patients. Only a minority of LARC patients responds completely to neoadjuvant treatments, thus avoiding invasive radical surgical resection. Moreover, toxic side effects can adversely affect patients' survival. The difficulty in separating in advances responder from non-responder patients affected by LARC highlights the need for valid biomarkers that guide clinical decision-making. In this context, microRNAs (miRNAs) seem to be promising candidates for predicting LARC prognosis and/or therapy response, particularly due to their stability, facile detection, and disease-specific expression in human tissues, blood, serum, or urine. Although a considerable number of studies involving potential miRNA predictors to nCRT have been conducted over the years, to date, the identification of the perfect miRNA signatures or single miRNA, as well as their use in the clinical practice, is still representing a challenge for the management of LARC patients. In this review, we will first introduce LARC and its difficult management. Then, we will trace the scientific history and the key obstacles for the identification of specific miRNAs that predict responsiveness to nCRT. There is a high potential to identify non-invasive biomarkers that circulate in the human bloodstream and that might indicate the LARC patients who benefit from the watch-and-wait approach. For this, we will critically evaluate recent advances dealing with cell-free nucleic acids including miRNAs and circulating tumor cells as prognostic or predictive biomarkers.

Model-based analysis of chromatin interactions from dCas9-Based CAPTURE-3C-seq

Deciphering long-range chromatin interactions is critical for understanding temporal and tissue-specific gene expression regulated by cis- and trans-acting factors. By combining the chromosome conformation capture (3C) and biotinylated dCas9 system, we previously established a method CAPTURE-3C-seq to unbiasedly identify high-resolution and locus-specific long-range DNA interactions. Here we present the statistical model and a flexible pipeline, C3S, for analysing CAPTURE-3C-seq or similar experimental data from raw sequencing reads to significantly interacting chromatin loci. C3S provides all steps for data processing, quality control and result illustration. It can automatically define the bin size based on the binding peak of the dCas9-targeted regions. Furthermore, it supports the analysis of intra- and inter-chromosomal interactions for different mammalian cell types. We successfully applied C3S across multiple datasets in human K562 cells and mouse embryonic stem cells (mESC) for detecting known and new chromatin interactions at multiple scales. Integrative and topological analysis of the interacted loci at the human β-globin gene cluster provides new insights into mechanisms in developmental gene regulation and network structure in local chromosomal architecture. Furthermore, computational results in mESCs reveal a role for chromatin interacting loops between enhancers and promoters in regulating alternative transcripts of the pluripotency gene OCT4.

Prediction of 3D Protein Structure Based on The Mutation of AKAP3 and PLOD3 Genes in The Case of Non-Obstructive Azoospermia

Background

The present study has been designed with the aim of evaluating A-kinase anchoring proteins 3 (AKAP3) and Procollagen-Lysine, 2-Oxoglutarate 5-Dioxygenase 3 (PLOD3) gene mutations and prediction of 3D protein structure for ligand binding activity in the cases of non-obstructive azoospermic male.

Materials and Methods

Clinically diagnosed cases of non-obstructive azoospermia (n=111) with age matched controls (n=42) were included in the present case-control study for genetics analysis and confirmation of diagnosis. The sample size was calculated using Epi info software version 6 with 90 power and 95% confidence interval. Genomic DNA was isolated from blood (2.0 ml) and a selected case was used for whole exome sequencing (WES) using Illumina Hiseq for identification of the genes. Bioinformatic tools were used for decode the amino acid sequence from biological database (www.ncbi.nlm.nih.gov/protein). 3D protein structure of AKAP3 and PLOD3 genes was predicted using I-TASSER server and binding energy was calculated by Ramachandran plot.

Results

Present study revealed the mutation of AKAP3 gene, showing frameshift mutation at rs67512580 (ACT → -CT) and loss of adenine in homozygous condition, where, leucine changed into serine. Similarly, PLOD3 gene shows missense mutation in heterozygous condition due to loss of guanine in the sequence AGG→A-G and it is responsible for the change in post-translational event of amino acid where arginine change into lysine. 3D structure shows 8 and 4 pockets binding site in AKAP3 and PLOD3 gene encoded proteins with MTX respectively, but only one site bound to the receptor with less binding energy representing efficient model of protein structure.

Conclusion

These genetic variations are responsible for alteration of translational events of amino acid sequences, leading to protein synthesis change following alteration in the predicted 3D structure and functions during spermiogen- esis, which might be a causative “risk” factor for male infertility.

Whole exome sequencing identifies compound heterozygous variants of CR2 gene in monozygotic twin patients with common variable immunodeficiency

Objectives:

A pair of female Malay monozygotic twins who presented with recurrent upper respiratory tract infections, hepatosplenomegaly, bronchiectasis and bicytopenia were recruited in this study. Both patients were suspected with primary immunodeficiency diseases. However, the definite diagnosis was not clear due to complex disease phenotypes. The objective of this study was to identify the causative gene mutation in these patients.

Methods:

Lymphocyte subset enumeration test and whole exome sequencing were performed.

Results:

We identified a compound heterozygous CR2 mutation (c.1916G>A and c.2012G>A) in both patients. These variants were then confirmed using Sanger sequencing.

Conclusion:

Whole exome sequencing analysis of the monozygotic twins revealed compound heterozygous missense mutations in CR2.

The MUC6/AP2A2 Locus and Its Relevance to Alzheimer's Disease: A Review

We recently reported evidence of Alzheimer's disease (AD)-linked genetic variation within the mucin 6 (MUC6) gene on chromosome 11p, nearby the adaptor-related protein complex 2 subunit alpha 2 (AP2A2) gene. This locus has interesting features related to human genomics and clinical research. MUC6 gene variants have been reported to potentially influence viral-including herpesvirus-immunity and the gut microbiome. Within the MUC6 gene is a unique variable number of tandem repeat (VNTR) region. We discovered an association between MUC6 VNTR repeat expansion and AD pathologic severity, particularly tau proteinopathy. Here, we review the relevant literature. The AD-linked VNTR polymorphism may also influence AP2A2 gene expression. AP2A2 encodes a polypeptide component of the adaptor protein complex, AP-2, which is involved in clathrin-coated vesicle function and was previously implicated in AD pathogenesis. To provide background information, we describe some key knowledge gaps in AD genetics research. The "missing/hidden heritability problem" of AD is highlighted. Extensive portions of the human genome, including the MUC6 VNTR, have not been thoroughly evaluated due to limitations of existing high-throughput sequencing technology. We present and discuss additional data, along with cautionary considerations, relevant to the hypothesis that MUC6 repeat expansion influences AD pathogenesis.

Association of PCSK1 gene polymorphisms with abdominal fat content in broilers

Protein proteolytic enzymes (Proprotein Convertase, PC) is a Ca²⁺ -dependent serine protease family, whose main function is to cleave precursors of biologically inactive proteins or peptide chains into active functional molecules. Proprotein convertase subtilisin/kexin type 1 (PCSK1) gene is mainly expressed in nerve and endocrine tissues. In this study, PCSK1 was selected as an important candidate gene for abdominal fat content in broilers. We cloned the exon region of chicken PCSK1 gene and found six single-nucleotide polymorphisms (SNPs). Association analysis was carried out and we found that the polymorphisms of these six SNPs were significantly associated with abdominal fat content in G19 and G20 populations. Five of these SNPs were significantly associated with abdominal fat content in G19 and G20 combined population. The polymorphism of these five SNPs was significantly correlated with the abdominal fat content of AA broilers. Together, our study demonstrated that c.927T>C, c.1880C>T, c.*900G>A, and c.*1164C>T were significantly associated with abdominal fat content in populations used in this study, which means that these SNPs in PCSK1 gene could be used as candidate markers to select lean broiler lines.

Copy Number Variations and Expression Levels of Guanylate-Binding Protein 6 Gene Associated with Growth Traits of Chinese Cattle

Association studies have indicated profound effects of copy number variations (CNVs) on various phenotypes in different species. In this study, we identified the CNV distributions and expression levels of guanylate-binding protein 6 (GBP6) associated with the growth traits of Chinese cattle. The results showed that the phenotypic values of body size and weight of Xianan (XN) cattle were higher than those of Nanyang (NY) cattle. The medium CNV types were mostly identified in the XN and NY breeds, but their CNV distributions were significantly different (adjusted p < 0.05). The association analysis revealed that the body weight, cannon circumference and chest circumference of XN cattle had significantly different values in different CNV types (p < 0.05), with CNV gain types (Log22-ΔΔCt > 0.5) displaying superior phenotypic values. We also found that transcription levels varied in different tissues (p < 0.001) and the CNV gain types showed the highest relative gene expression levels in the muscle tissue, consistent with the highest phenotypic values of body weight and cannon circumference among the three CNV types. Consequently, our results suggested that CNV gain types of GBP6 could be used as the candidate markers in the cattle-breeding program for growth traits.

Genome-Wide Genotype-Expression Relationships Reveal Both Copy Number and Single Nucleotide Differentiation Contribute to Differential Gene Expression between Stickleback Ecotypes

Repeated and independent emergence of trait divergence that matches habitat differences is a sign of parallel evolution by natural selection. Yet, the molecular underpinnings that are targeted by adaptive evolution often remain elusive. We investigate this question by combining genome-wide analyses of copy number variants (CNVs), single nucleotide polymorphisms (SNPs), and gene expression across four pairs of lake and river populations of the three-spined stickleback (Gasterosteus aculeatus). We tested whether CNVs that span entire genes and SNPs occurring in putative cis-regulatory regions contribute to gene expression differences between sticklebacks from lake and river origins. We found 135 gene CNVs that showed a significant positive association between gene copy number and gene expression, suggesting that CNVs result in dosage effects that can fuel phenotypic variation and serve as substrates for habitat-specific selection. Copy number differentiation between lake and river sticklebacks also contributed to expression differences of two immune-related genes in immune tissues, cathepsin A and GIMAP7. In addition, we identified SNPs in cis-regulatory regions (eSNPs) associated with the expression of 1,865 genes, including one eSNP upstream of a carboxypeptidase gene where both the SNP alleles differentiated and the gene was differentially expressed between lake and river populations. Our study highlights two types of mutations as important sources of genetic variation involved in the evolution of gene expression and in potentially facilitating repeated adaptation to novel environments.

Molecular dynamics simulations for genetic interpretation in protein coding regions: where we are, where to go and when

The increasing ease with which massive genetic information can be obtained from patients or healthy individuals has stimulated the development of interpretive bioinformatics tools as aids in clinical practice. Most such tools analyze evolutionary information and simple physical-chemical properties to predict whether replacement of one amino acid residue with another will be tolerated or cause disease. Those approaches achieve up to 80-85% accuracy as binary classifiers (neutral/pathogenic). As such accuracy is insufficient for medical decision to be based on, and it does not appear to be increasing, more precise methods, such as full-atom molecular dynamics (MD) simulations in explicit solvent, are also discussed. Then, to describe the goal of interpreting human genetic variations at large scale through MD simulations, we restrictively refer to all possible protein variants carrying single-amino-acid substitutions arising from single-nucleotide variations as the human variome. We calculate its size and develop a simple model that allows calculating the simulation time needed to have a 0.99 probability of observing unfolding events of any unstable variant. The knowledge of that time enables performing a binary classification of the variants (stable-potentially neutral/unstable-pathogenic). Our model indicates that the human variome cannot be simulated with present computing capabilities. However, if they continue to increase as per Moore's law, it could be simulated (at 65°C) spending only 3 years in the task if we started in 2031. The simulation of individual protein variomes is achievable in short times starting at present. International coordination seems appropriate to embark upon massive MD simulations of protein variants.

Review of applications of high-throughput sequencing in personalized medicine: barriers and facilitators of future progress in research and clinical application

There has been an exponential growth in the performance and output of sequencing technologies (omics data) with full genome sequencing now producing gigabases of reads on a daily basis. These data may hold the promise of personalized medicine, leading to routinely available sequencing tests that can guide patient treatment decisions. In the era of high-throughput sequencing (HTS), computational considerations, data governance and clinical translation are the greatest rate-limiting steps. To ensure that the analysis, management and interpretation of such extensive omics data is exploited to its full potential, key factors, including sample sourcing, technology selection and computational expertise and resources, need to be considered, leading to an integrated set of high-performance tools and systems. This article provides an up-to-date overview of the evolution of HTS and the accompanying tools, infrastructure and data management approaches that are emerging in this space, which, if used within in a multidisciplinary context, may ultimately facilitate the development of personalized medicine.

m6AVar: a database of functional variants involved in m6A modification

Identifying disease-causing variants among a large number of single nucleotide variants (SNVs) is still a major challenge. Recently, N⁶-methyladenosine (m⁶A) has become a research hotspot because of its critical roles in many fundamental biological processes and a variety of diseases. Therefore, it is important to evaluate the effect of variants on m⁶A modification, in order to gain a better understanding of them. Here, we report m6AVar (http://m6avar.renlab.org), a comprehensive database of m⁶A-associated variants that potentially influence m⁶A modification, which will help to interpret variants by m⁶A function. The m⁶A-associated variants were derived from three different m⁶A sources including miCLIP/PA-m⁶A-seq experiments (high confidence), MeRIP-Seq experiments (medium confidence) and transcriptome-wide predictions (low confidence). Currently, m6AVar contains 16 132 high, 71 321 medium and 326 915 low confidence level m⁶A-associated variants. We also integrated the RBP-binding regions, miRNA-targets and splicing sites associated with variants to help users investigate the effect of m⁶A-associated variants on post-transcriptional regulation. Because it integrates the data from genome-wide association studies (GWAS) and ClinVar, m6AVar is also a useful resource for investigating the relationship between the m⁶A-associated variants and disease. Overall, m6AVar will serve as a useful resource for annotating variants and identifying disease-causing variants.

Evolutionary Changes in Transcriptional Regulation: Insights into Human Behavior and Neurological Conditions

Understanding the biological basis for human-specific cognitive traits presents both immense challenges and unique opportunities. Although the question of what makes us human has been investigated with several different methods, the rise of comparative genomics, epigenomics, and medical genetics has provided tools to help narrow down and functionally assess the regions of the genome that seem evolutionarily relevant along the human lineage. In this review, we focus on how medical genetic cases have provided compelling functional evidence for genes and loci that appear to have interesting evolutionary signatures in humans. Furthermore, we examine a special class of noncoding regions, human accelerated regions (HARs), that have been suggested to show human-lineage-specific divergence, and how the use of clinical and population data has started to provide functional information to examine these regions. Finally, we outline methods that provide new insights into functional noncoding sequences in evolution.

Treatment resistance in urothelial carcinoma: an evolutionary perspective

The emergence of treatment-resistant clones is a critical barrier to cure in patients with urothelial carcinoma. Setting the stage for the evolution of resistance, urothelial carcinoma is characterized by extensive mutational heterogeneity, which is detectable even in patients with early stage disease. Chemotherapy and immunotherapy both act as selective pressures that shape the evolutionary trajectory of urothelial carcinoma throughout the course of the disease. A detailed understanding of the dynamics of evolutionary drivers is required for the rational development of curative therapies. Herein, we describe the molecular basis of the clonal evolution of urothelial carcinomas and the use of genomic approaches to predict treatment responses. We discuss various mechanisms of resistance to chemotherapy with a focus on the mutagenic effects of the DNA dC->dU-editing enzymes APOBEC3 family of proteins. We also review the evolutionary mechanisms underlying resistance to immunotherapy, such as the loss of clonal tumour neoantigens. By dissecting treatment resistance through an evolutionary lens, the field will advance towards true precision medicine for urothelial carcinoma.

Origins of Intraindividual Genetic Variation in Human Fetuses

BACKGROUND

Intraindividual copy number variation (CNV) origin is largely unknown. They might be due to aging and/or common genome instability at the preimplantation stage while contribution of preimplantation in human intraindividual CNVs occurrence is unknown. To address this question, we investigated mosaicism and its origin in the fetuses of natural conception.

METHODS

We studied normal fetuses following therapeutic abortion due to maternal indications. We analyzed the genome of 22 tissues of each fetus by array comparative genomic hybridization for intraindividual CNVs. Each tissue was studied in 2 microarray experiments; the reciprocal aberrations larger than 40 Kb, identified by comparing tissues of each fetus, were subsequently validated using quantitative polymerase chain reaction.

RESULTS

Through intraindividual comparison, frequency of reciprocal events varied from 2 to 9. According to the distribution pattern of the frequent CNV in derivatives of different germ layers, we found that its origin is early development including preimplantation, whereas CNVs with low frequency have occurred in later stages. Shared CNVs in both fetuses were belonged to thymus and related to the functional role of genes located in these CNVs.

CONCLUSIONS

The origin of some of fetal CNVs is preimplantation stage. Each organ might inherit CNVs with an unpredictable pattern due to the extensive cell mixing/migration in embryonic development.

Towards a map of cis-regulatory sequences in the human genome

Accumulating evidence indicates that transcription factor (TF) binding sites, or cis-regulatory elements (CREs), and their clusters termed cis-regulatory modules (CRMs) play a more important role than do gene-coding sequences in specifying complex traits in humans, including the susceptibility to common complex diseases. To fully characterize their roles in deriving the complex traits/diseases, it is necessary to annotate all CREs and CRMs encoded in the human genome. However, the current annotations of CREs and CRMs in the human genome are still very limited and mostly coarse-grained, as they often lack the detailed information of CREs in CRMs. Here, we integrated 620 TF ChIP-seq datasets produced by the ENCODE project for 168 TFs in 79 different cell/tissue types and predicted an unprecedentedly completely map of CREs in CRMs in the human genome at single nucleotide resolution. The map includes 305 912 CRMs containing a total of 1 178 913 CREs belonging to 736 unique TF binding motifs. The predicted CREs and CRMs tend to be subject to either purifying selection or positive selection, thus are likely to be functional. Based on the results, we also examined the status of available ChIP-seq datasets for predicting the entire regulatory genome of humans.