Pathogenic variants in human DNA damage repair genes mostly arose after the latest human out-of-Africa migration.

Introduction: The DNA damage repair (DDR) system in human genome is pivotal in maintaining genomic integrity. Pathogenic variation (PV) in DDR genes impairs their function, leading to genome instability and increased susceptibility to diseases, especially cancer. Understanding the evolution origin and arising time of DDR PV is crucial for comprehending disease susceptibility in modern humans. Methods: We used big data approach to identify the PVs in DDR genes in modern humans. We mined multiple genomic databases derived from 251,214 modern humans of African and non-Africans. We compared the DDR PVs between African and non-African. We also mined the DDR PVs in the genomic data derived from 5,031 ancient humans. We used the DDR PVs from ancient humans as the intermediate to further the DDR PVs between African and non-African. Results and discussion: We identified 1,060 single-base DDR PVs across 77 DDR genes in modern humans of African and non-African. Direct comparison of the DDR PVs between African and non-African showed that 82.1% of the non-African PVs were not present in African. We further identified 397 single-base DDR PVs in 56 DDR genes in the 5,031 ancient humans dated between 45,045 and 100 years before present (BP) lived in Eurasian continent therefore the descendants of the latest out-of-Africa human migrants occurred 50,000-60,000 years ago. By referring to the ancient DDR PVs, we observed that 276 of the 397 (70.3%) ancient DDR PVs were exclusive in non-African, 106 (26.7%) were shared between non-African and African, and only 15 (3.8%) were exclusive in African. We further validated the distribution pattern by testing the PVs in BRCA and TP53, two of the important genes in genome stability maintenance, in African, non-African, and Ancient humans. Our study revealed that DDR PVs in modern humans mostly emerged after the latest out-of-Africa migration. The data provides a foundation to understand the evolutionary basis of disease susceptibility, in particular cancer, in modern humans.

Pathogenic variants in human DNA damage repair genes mostly arose in recent human history.

BACKGROUND: Genome stability is maintained by the DNA damage repair (DDR) system composed of multiple DNA repair pathways of hundreds of genes. Germline pathogenic variation (PV) in DDR genes damages function of the affected DDR genes, leading to genome instability and high risk of diseases, in particular, cancer. Knowing evolutionary origin of the PVs in human DDR genes is essential to understand the etiology of human diseases. However, answer to the issue remains largely elusive. In this study, we analyzed evolutionary origin for the PVs in human DDR genes. METHODS: We identified 169 DDR genes by referring to various databases and identified PVs in the DDR genes of modern humans from ClinVar database. We performed a phylogenetic analysis to analyze the conservation of human DDR PVs in 100 vertebrates through cross-species genomic data comparison using the phyloFit program of the PHAST package and visualized the results using the GraphPad Prism software and the ggplot module. We identified DDR PVs from over 5000 ancient humans developed a database to host the DDR PVs ( https://genemutation.fhs.um.edu.mo/dbDDR-AncientHumans ). Using the PV data, we performed a molecular archeological analysis to compare the DDR PVs between modern humans and ancient humans. We analyzed evolution selection of DDR genes across 20 vertebrates using the CodeML in PAML for phylogenetic analysis. RESULTS: Our phylogenic analysis ruled out cross-species conservation as the origin of human DDR PVs. Our archeological approach identified rich DDR PVs shared between modern and ancient humans, which were mostly dated within the last 5000 years. We also observed similar pattern of quantitative PV distribution between modern and ancient humans. We further detected a set of ATM, BRCA2 and CHEK2 PVs shared between human and Neanderthals. CONCLUSIONS: Our study reveals that human DDR PVs mostly arose in recent human history. We propose that human high cancer risk caused by DDR PVs can be a by-product of human evolution.

Using Portuguese BRCA pathogenic variation as a model to study the impact of human admixture on human health.

BACKGROUND: Admixture occurs between different ethnic human populations. The global colonization in recent centuries by Europeans led to the most significant admixture in human history. While admixture may enhance genetic diversity for better fitness, it may also impact on human health by transmitting genetic variants for disease susceptibility in the admixture population. The admixture by Portuguese global exploration initiated in the 15th century has reached over 20 million of Portuguese-heritage population worldwide. It provides a valuable model to study the impact of admixture on human health. BRCA1 and BRCA2 (BRCA) are two of the important tumor suppressor genes. The pathogenic variation (PV) in BRCA is well determined to cause high risk of hereditary breast and ovarian cancer. Tracing the distribution of Portuguese BRCA PV in Portuguese-heritage population will help to understand the impact of admixture on cancer susceptibility in modern humans. In this study, we analyzed the distribution of the Portuguese-originated BRCA variation in Brazilian population, which has high degree Portuguese-heritage. METHODS: By comprehensive data mining, standardization and annotation, we generated a Portuguese-derived BRCA variation dataset and a Brazilian-derived BRCA variation dataset. We compared the two BRCA variation datasets to identify the BRCA variants shared between the two populations. RESULTS: The Portuguese-derived BRCA variation dataset consists of 220 BRCA variants including 78 PVs from 11,482 Portuguese cancer patients, 93 (42.2%) in BRCA1 and 127 (57.7%) in BRCA2. Of the 556 Portuguese BRCA PV carriers carrying the 78 PVs, 331 (59.5%) carried the three Portuguese-BRCA founder PVs of BRCA1 c.2037delinsCC, BRCA1 c.3331_3334del and BRCA2 c.156_157insAlu. The Brazilian-derived BRCA variation dataset consists of 255 BRCA PVs from 7,711 cancer patients, 136 (53.3%) in BRCA1 and 119 (46.6%) in BRCA2. We developed an open database named dbBRCA-Portuguese ( https://genemutation.fhs.um.edu.mo/dbbrca-portuguese/ ) and an open database named dbBRCA-Brazilian ( https://genemutation.fhs.um.edu.mo/dbbrca-brazilian ) to host the BRCA variation data from Portuguese and Brazilian populations. We compared the BRCA PV datasets between Portuguese and Brazilian populations, and identified 29 Portuguese-specific BRCA PVs shared between Portuguese and Brazilian populations, 14 in BRCA1 including the Portuguese founder BRCA1 c.3331_3334del and BRCA1 c.2037delinsCC, and 15 in BRCA2 including the Portuguese founder BRCA2 c.156_157insAlu. Searching the 78 Portuguese BRCA PVs in over 5,000 ancient human genomes identified evolution origin for only 8 PVs in Europeans dated between 37,470 and 3,818 years before present, confirming the Portuguese-specificity of Portuguese BRCA PVs; comparing the 78 Portuguese BRCA PVs Portuguese, 255 Brazilian BRCA PVs, and 134 African BRCA PVs showed little overlapping, ruling out the possibility that the BRCA PVs shared between Portuguese and Brazilian may also be contributed by African. CONCLUSION: Our study provides evidence that the admixture in recent human history contributed to cancer susceptibility in modern humans.

Evolutionary origin of germline pathogenic variants in human DNA mismatch repair genes.

BACKGROUND: Mismatch repair (MMR) system is evolutionarily conserved for genome stability maintenance. Germline pathogenic variants (PVs) in MMR genes that lead to MMR functional deficiency are associated with high cancer risk. Knowing the evolutionary origin of germline PVs in human MMR genes will facilitate understanding the biological base of MMR deficiency in cancer. However, systematic knowledge is lacking to address the issue. In this study, we performed a comprehensive analysis to know the evolutionary origin of human MMR PVs. METHODS: We retrieved MMR gene variants from the ClinVar database. The genomes of 100 vertebrates were collected from the UCSC genome browser and ancient human sequencing data were obtained through comprehensive data mining. Cross-species conservation analysis was performed based on the phylogenetic relationship among 100 vertebrates. Rescaled ancient sequencing data were used to perform variant calling for archeological analysis. RESULTS: Using the phylogenetic approach, we traced the 3369 MMR PVs identified in modern humans in 99 non-human vertebrate genomes but found no evidence for cross-species conservation as the source for human MMR PVs. Using the archeological approach, we searched the human MMR PVs in over 5000 ancient human genomes dated from 45,045 to 100 years before present and identified a group of MMR PVs shared between modern and ancient humans mostly within 10,000 years with similar quantitative patterns. CONCLUSION: Our study reveals that MMR PVs in modern humans were arisen within the recent human evolutionary history.

Classification of MLH1 Missense VUS Using Protein Structure-Based Deep Learning-Ramachandran Plot-Molecular Dynamics Simulations Method.

Pathogenic variation in DNA mismatch repair (MMR) gene MLH1 is associated with Lynch syndrome (LS), an autosomal dominant hereditary cancer. Of the 3798 MLH1 germline variants collected in the ClinVar database, 38.7% (1469) were missense variants, of which 81.6% (1199) were classified as Variants of Uncertain Significance (VUS) due to the lack of functional evidence. Further determination of the impact of VUS on MLH1 function is important for the VUS carriers to take preventive action. We recently developed a protein structure-based method named "Deep Learning-Ramachandran Plot-Molecular Dynamics Simulation (DL-RP-MDS)" to evaluate the deleteriousness of MLH1 missense VUS. The method extracts protein structural information by using the Ramachandran plot-molecular dynamics simulation (RP-MDS) method, then combines the variation data with an unsupervised learning model composed of auto-encoder and neural network classifier to identify the variants causing significant change in protein structure. In this report, we applied the method to classify 447 MLH1 missense VUS. We predicted 126/447 (28.2%) MLH1 missense VUS were deleterious. Our study demonstrates that DL-RP-MDS is able to classify the missense VUS based solely on their impact on protein structure.

Classification of PTEN missense VUS through exascale simulations.

Phosphatase and tensin homolog (PTEN), a tumor suppressor with dual phosphatase properties, is a key factor in PI3K/AKT signaling pathway. Pathogenic germline variation in PTEN can abrogate its ability to dephosphorylate, causing high cancer risk. Lack of functional evidence lets numerous PTEN variants be classified as variants of uncertain significance (VUS). Utilizing Molecular Dynamics (MD) simulations, we performed a thorough evaluation for 147 PTEN missense VUS, sorting them into 66 deleterious and 81 tolerated variants. Utilizing replica exchange molecular dynamic (REMD) simulations, we further assessed the variants situated in the catalytic core of PTEN's phosphatase domain and uncovered conformational alterations influencing the structural stability of the phosphatase domain. There was a high degree of agreement between our results and the variants classified by Variant Abundance by Massively Parallel Sequencing, saturation mutagenesis, multiplexed functional data and experimental assays. Our extensive analysis of PTEN missense VUS should benefit their clinical applications in PTEN-related cancer. SIGNIFICANCE STATEMENT: Classification of PTEN variants affecting its lipid phosphatase activity is important for understanding the roles of PTEN variation in the pathogenesis of hereditary and sporadic malignancies. Of the 3000 variants identified in PTEN, 1296 (43%) were assigned as VUS. Here, we applied MD and REMD simulations to investigate the effects of PTEN missense VUS on the structural integrity of the PTEN phosphatase domain consisting the WPD, P and TI active sites. We classified a total of 147 missense VUS into 66 deleterious and 81 tolerated variants by referring to the control group comprising 54 pathogenic and 12 benign variants. The classification was largely in concordance with these classified by experimental approaches.

Evolutionary Origin of Human PALB2 Germline Pathogenic Variants.

PALB2 (Partner and localizer of BRCA2) is crucial for repairing DNA double-stranded breaks (DSBs) through homologous recombination (HR). Germline pathogenic variation in PALB2 disrupts DNA damage repair and increases the risk of Fanconi Anemia, breast cancer, and ovarian cancer. Determination of the evolutionary origin of human PALB2 variants will promote a deeper understanding of the biological basis of PALB2 germline variation and its roles in human diseases. We tested the evolution origin for 1444 human PALB2 germline variants, including 484 pathogenic and 960 benign variants. We performed a phylogenic analysis by tracing the variants in 100 vertebrates. However, we found no evidence to show that cross-species conservation was the origin of PALB2 germline pathogenic variants, but it is indeed a rich source for PALB2 germline benign variants. We performed a paleoanthropological analysis by tracing the variants in over 5000 ancient humans. We identified 50 pathogenic in 71 ancient humans dated from 32,895 to 689 before the present, of which 90.1% were dated within the recent 10,000 years. PALB2 benign variants were also highly shared with ancient humans. Data from our study reveal that human PALB2 pathogenic variants mostly arose in recent human history.

TP53 germline pathogenic variants in modern humans were likely originated during recent human history.

TP53 is crucial for maintaining genome stability and preventing oncogenesis. Germline pathogenic variation in TP53 damages its function, causing genome instability and increased cancer risk. Despite extensive study in TP53, the evolutionary origin of the human TP53 germline pathogenic variants remains largely unclear. In this study, we applied phylogenetic and archaeological approaches to identify the evolutionary origin of TP53 germline pathogenic variants in modern humans. In the phylogenic analysis, we searched 406 human TP53 germline pathogenic variants in 99 vertebrates distributed in eight clades of Primate, Euarchontoglires, Laurasiatheria, Afrotheria, Mammal, Aves, Sarcopterygii and Fish, but we observed no direct evidence for the cross-species conservation as the origin; in the archaeological analysis, we searched the variants in 5031 ancient human genomes dated between 45045 and 100 years before present, and identified 45 pathogenic variants in 62 ancient humans dated mostly within the last 8000 years; we also identified 6 pathogenic variants in 3 Neanderthals dated 44000 to 38515 years before present and 1 Denisovan dated 158 550 years before present. Our study reveals that TP53 germline pathogenic variants in modern humans were likely originated in recent human history and partially inherited from the extinct Neanderthals and Denisovans.

DARVIC: Dihedral angle-reliant variant impact classifier for functional prediction of missense VUS.

BACKGROUND: Of the large number of genetic variants identified, the functional impact for most of them remains unknown. Mutations in DNA damage repair genes such as MUTYH, which is involved in repairing A:8-oxoG mismatches caused by reactive oxygen species, can cause a higher risk of cancer. Mutations happening in other key genes such as TP53 also pose huge health threats and risk of cancer. The interpretation of genetic variants' functional impact is a forefront issue that needs to be addressed. Many different in silico methods based on different principles have been developed and applied in interpreting genetic variants. However, a current challenge is that many existing methods tend to overpredict the pathogenicity of benign variants. A new approach is needed to tackle this issue to improve genetic variant interpretation through the use of in silico methods. METHODS: In this study, we developed another protein structural-based approach called Dihedral angle-reliant variant impact classifier (DARVIC) to predict the deleterious impact of the coding-changing missense variants. DARVIC uses Ramachandran's principle of protein stereochemistry as the theoretical foundation and uses molecular dynamics simulations coupled with a supervised machine learning algorithm XGBoost to determine the functional impact of missense variants on protein structural stability. RESULTS: We characterized the features of dihedral angles in dynamic protein structures. We also tested the performance of DARVIC in MUTYH and TP53 missense variants and achieved satisfactory results in reflecting the functional impacts of the variants on protein structure. The method achieved a balanced accuracy of 84% in a functionally validated MUTYH dataset containing both benign and pathogenic missense variants, higher than other existing in silico methods. Along with that, DARVIC was able to predict 119 (47%) deleterious variants from a dataset of 254 MUTYH VUS. Further application of DARVIC to a functionally validated TP53 dataset had a balanced accuracy of 94%, topping other methods, demonstrating DARVIC's robustness. CONCLUSION: DARVIC provides a valuable tool to predict the functional impacts of missense variants based on their effects on protein structural stability and motion. At its current state, DARVIC performed well in predicting the functional impact of the missense variants both in MUTYH and TP53. We expect its high potential to predict functional impact for the missense variants in other genes.

Etiological roles of core promoter variation in triple-negative breast cancer.

Abnormal gene expression plays key role in cancer development. A core promoter is located around the transcriptional start site. Through interaction between core promoter sequences and transcriptional factors, core promoter controls transcriptional initiation. We hypothesized that in cancer, core promoter sequences could be mutated to interfere the interaction with transcriptional factors, resulting in altered transcriptional initiation and abnormal gene expression and cancer development. We used triple-negative breast cancer (TNBC) as a model to test our hypothesis. We collected genome-wide core promoter variants from 279 TNBC genomes. After extensive filtering of normal genomic polymorphism, we identified 19,427 recurrent somatic variants in 1,238 core promoters of 1,274 genes and 1,694 recurrent germline variants in 272 core promoters of 294 genes. Many of the affected genes were oncogenes and tumor suppressors. Analysis of RNA-seq data from the same patient cohort identified increased or decreased gene expression in 439 somatic and 85 germline variants-affected genes, and the results were validated by luciferase reporter assay. By comparing with the core promoter variation data from 610 unclassified breast cancer, we observed that core promoter variants in TNBC were highly TNBC-specific. We further identified the drugs targeting the genes with core promoter variation. Our study demonstrates that core promoter is highly mutable in cancer, and can play etiological roles in TNBC and other types of cancer through influencing transcriptional initiation.

Integration of deep learning with Ramachandran plot molecular dynamics simulation for genetic variant classification.

Functional classification of genetic variants is a key for their clinical applications in patient care. However, abundant variant data generated by the next-generation DNA sequencing technologies limit the use of experimental methods for their classification. Here, we developed a protein structure and deep learning (DL)-based system for genetic variant classification, DL-RP-MDS, which comprises two principles: 1) Extracting protein structural and thermodynamics information using the Ramachandran plot-molecular dynamics simulation (RP-MDS) method, 2) combining those data with an unsupervised learning model of auto-encoder and a neural network classifier to identify the statistical significance patterns of the structural changes. We observed that DL-RP-MDS provided higher specificity than over 20 widely used in silico methods in classifying the variants of three DNA damage repair genes: TP53, MLH1, and MSH2. DL-RP-MDS offers a powerful platform for high-throughput genetic variant classification. The software and online application are available at https://genemutation.fhs.um.edu.mo/DL-RP-MDS/.

Evolutionary Origin of MUTYH Germline Pathogenic Variations in Modern Humans.

MUTYH plays an essential role in preventing oxidation-caused DNA damage. Pathogenic germline variations in MUTYH damage its function, causing intestinal polyposis and colorectal cancer. Determination of the evolutionary origin of the variation is essential to understanding the etiological relationship between MUTYH variation and cancer development. In this study, we analyzed the origins of pathogenic germline variants in human MUTYH. Using a phylogenic approach, we searched MUTYH pathogenic variants in modern humans in the MUTYH of 99 vertebrates across eight clades. We did not find pathogenic variants shared between modern humans and the non-human vertebrates following the evolutionary tree, ruling out the possibility of cross-species conservation as the origin of human pathogenic variants in MUTYH. We then searched the variants in the MUTYH of 5031 ancient humans and extinct Neanderthals and Denisovans. We identified 24 pathogenic variants in 42 ancient humans dated between 30,570 and 480 years before present (BP), and three pathogenic variants in Neanderthals dated between 65,000 and 38,310 years BP. Data from our study revealed that human MUTYH pathogenic variants mostly arose in recent human history and partially originated from Neanderthals.

Pancreatic cancer cluster region identified in BRCA2.

Pancreatic cancer has a poor prognosis. Lack of diagnostic markers prevents its early diagnosis and treatment. Pathogenic germline variation in BRCA1 and BRCA2 (BRCA) is genetic predisposition for cancer. The location of variants in different regions in BRCA is non-randomly enriched in different types of cancer as shown by the breast cancer cluster region (BCCR), ovarian cancer cluster region (OCCR) and prostate cancer cluster region (PrCCR). Although pathogenic BRCA variation also contributes to pancreatic cancer, no pancreatic cancer cluster region (PcCCR) in BRCA1 or BRCA2 has been identified due to the relatively low incidence of pancreatic cancer and the lack of sufficient variation data from pancreatic cancer. Through comprehensive data mining, we identified 215 BRCA pathogenic variants (PVs) (71 in BRCA1 and 144 in BRCA2) from 27 118 pancreatic cancer cases. Through mapping the variants, we identified a region non-randomly enriched in pancreatic cancer between BRCA2 c.3515 and c.6787. This region contained 59 BRCA2 PVs and included 57% of pancreatic cancer cases (95% CI 43% to 70%). The PcCCR did not overlap with the BCCR and PrCCR but overlapped with the BRCA2 OCCR, highlighting that this region may play similar aetiological roles in pancreatic cancer and ovarian cancer.

Ethnic-specificity, evolution origin and deleteriousness of Asian BRCA variation revealed by over 7500 BRCA variants derived from Asian population.

Pathogenic variation in BRCA1 and BRCA2 (BRCA) causes high risk of breast and ovarian cancer, and BRCA variation data are important markers for BRCA-related clinical cancer applications. However, comprehensive BRCA variation data are lacking from the Asian population despite its large population size, heterogenous genetic background and diversified living environment across the Asia continent. We performed a systematic study on BRCA variation in Asian population including extensive data mining, standardization, annotation and characterization. We identified 7587 BRCA variants from 685 592 Asian individuals in 40 Asia countries and regions, including 1762 clinically actionable pathogenic variants and 4915 functionally unknown variants (https://genemutation.fhs.um.edu.mo/Asian-BRCA/). We observed the highly ethnic-specific nature of Asian BRCA variants between Asian and non-Asian populations and within Asian populations, highlighting that the current European descendant population-based BRCA data is inadequate to reflect BRCA variation in the Asian population. We also provided archeological evidence for the evolutionary origin and arising time of Asian BRCA variation. We further provided structural-based evidence for the deleterious variants enriched within the functionally unknown Asian BRCA variants. The data from our study provide a current view of BRCA variation in the Asian population and a rich resource to guide clinical applications of BRCA-related cancer for the Asian population.

Core promoter in TNBC is highly mutated with rich ethnic signature.

The core promoter plays an essential role in regulating transcription initiation by controlling the interaction between transcriptional factors and sequence motifs in the core promoter. Although mutation in core promoter sequences is expected to cause abnormal gene expression leading to pathogenic consequences, limited supporting evidence showed the involvement of core promoter mutation in diseases. Our previous study showed that the core promoter is highly polymorphic in worldwide human ethnic populations in reflecting human history and adaptation. Our recent characterization of the core promoter in triple-negative breast cancer (TNBC), a subtype of breast cancer, in a Chinese TNBC cohort revealed the wide presence of core promoter mutation in TNBC. In the current study, we analyzed the core promoter in a Thai TNBC cohort. We also observed rich core promoter mutation in the Thai TNBC patients. We compared the core promoter mutations between Chinese and Thai TNBC cohorts. We observed substantial differences of core promoter mutation in TNBC between the two cohorts, as reflected by the mutation spectrum, mutation-effected gene and functional category, and altered gene expression. Our study confirmed that the core promoter in TNBC is highly mutable, and is highly ethnic-specific.

The BRCAness Landscape of Cancer.

BRCAness refers to the damaged homologous recombination (HR) function due to the defects in HR-involved non-BRCA1/2 genes. BRCAness is the important marker for the use of synthetic lethal-based PARP inhibitor therapy in breast and ovarian cancer treatment. The success provides an opportunity of applying PARP inhibitor therapy to treat other cancer types with BRCAness features. However, systematic knowledge is lack for BRCAness in different cancer types beyond breast and ovarian cancer. We performed a comprehensive characterization for 40 BRCAness-related genes in 33 cancer types with over 10,000 cancer cases, including pathogenic variation, homozygotic deletion, promoter hypermethylation, gene expression, and clinical correlation of BRCAness in each cancer type. Using BRCA1/BRCA2 mutated breast and ovarian cancer as the control, we observed that BRCAness is widely present in multiple cancer types. Based on the sum of the BRCAneass features in each cancer type, we identified the following 21 cancer types as the potential targets for PARPi therapy: adrenocortical carcinoma, bladder urothelial carcinoma, brain lower grade glioma, colon adenocarcinoma, esophageal carcinoma, head and neck squamous carcinoma, kidney chromophobe, kidney renal clear cell carcinoma, kidney renal papillary cell carcinoma, liver hepatocellular carcinoma, lung adenocarcinoma, lung squamous cell carcinoma, mesothelioma, rectum adenocarcinoma, pancreatic adenocarcinoma, prostate adenocarcinoma, sarcoma, skin cutaneous melanoma, stomach adenocarcinoma, uterine carcinosarcoma, and uterine corpus endometrial carcinoma.

Applications of Molecular Dynamics Simulation in Protein Study.

Molecular Dynamics (MD) Simulations is increasingly used as a powerful tool to study protein structure-related questions. Starting from the early simulation study on the photoisomerization in rhodopsin in 1976, MD Simulations has been used to study protein function, protein stability, protein-protein interaction, enzymatic reactions and drug-protein interactions, and membrane proteins. In this review, we provide a brief review for the history of MD Simulations application and the current status of MD Simulations applications in protein studies.

Heterozygotic Brca1 mutation initiates mouse genome instability at embryonic stage.

BRCA1 mutation is the genetic predisposition in causing genome instability towards cancer. BRCA1 mutation is predominantly germline inherited at the fertilization. However, when the inherited mutation initiates genome instability in the mutation carriers remains largely elusive. We used a heterozygotic Brca1-knockout mouse as a model to investigate the issue. Through whole-genome sequencing and bioinformatics analysis, we monitored genome status across the developmental stages from embryo to adulthood in the mouse model. We observed that genome instability as reflected by structural variation, indel and copy number variation already appeared at 10.5-day embryo and progressively towards adulthood. We also observed that the genome instability was not linearly accumulated but dynamically changed along the developmental process, affecting many oncogenic genes and pathways including DNA damage repair, estrogen signaling, and oncogenesis. We further observed that many genome abnormalities in the cancer caused by Brca1 mutation were originated at embryonic stage, and Trp53 (TP53) mutation was not essential for the Brca1 mutation-caused genome instability in the non-cancer cells. Our study revealed that heterozygotic Brca1 mutation alone can cause genome instability at embryonic stage, highlighting that prevention of BRCA1 mutation-related cancer in humans may need to start earlier than currently considered.

Distinct landscapes of deleterious variants in DNA damage repair system in ethnic human populations.

Deleterious variants in DNA damage repair (DDR) system can cause genome instability and increase cancer risk. In this study, we analyzed the deleterious variants in DDR system in 16 ethnic human populations. From the genetic variants in 169 DDR genes involved in nine DDR pathways collected from 158,612 individuals of different ethnic background, we identified 1,781 deleterious variants in 81 DDR genes in eight DDR pathways (https://genemutation.fhs.um.edu.mo/dbddr-global/). Our analysis showed although the quantity of deleterious variants was loaded at a similar level, the landscape of the variants differed substantially among different populations that two-third of the variants were present in single ethnic populations, and the rest was mostly shared between the populations with closer geographic and genetic relationship. The highly ethnic-specific DDR deleterious variation suggests its potential relationship with different disease susceptibility in ethnic human populations.

Identification of deleterious variants of uncertain significance in BRCA2 BRC4 repeat through molecular dynamics simulations.

Large quantity of variants of uncertain significance (VUS) has been identified in cancer predisposition genes, but classification of VUS remains a big challenge. We proposed that the impact of VUS on protein structure stability can be used to identify these with deleterious effects by using molecular dynamics simulation (MDS)-based approach and developed a MDS-based method for missense VUS classification. In the current study, we applied the system to classify the missense VUS in BRCA2. BRCA2 plays an important role in maintaining genome stability by repairing double-strand DNA damage through homologous recombination. BRCA2 BRC repeats bring RAD51 from cytoplasm to the break sites in nucleus to initiate the repairing process. Missense variants in BRCA2 BRC repeats can interfere the interaction between BRCA2 and RAD51, impair double-strand break repair, cause genome instability and increase cancer risk. We characterized the missense VUS in BRCA2 BRC4 repeat, the primary site of BRCA2 interacting with RAD51. Based on the well-determined BRC4 structure, we applied MDS to measure the impact of BRC4 missense VUS on the stability of BRC4 structure by testing the equilibrium state, flexibility, compactness, hydrogen bonds and surface accessibility. Of the 46 missense VUS analyzed, we were able to differentiate them into 24 Deleterious and 22 Tolerated variants. Comparison between the MDS-based and other 24 existing computational methods for variant classification showed that the MDS-based approach is highly sensitive and specific for classifying missense VUS in cancer predisposition genes.