Re-evaluating experimental validation in the Big Data Era : a conceptual argument

Non peer reviewe

Can We Assume the Gene Expression Profile as a Proxy for Signaling Network Activity?

Studying relationships among gene products by expression profile analysis is a common approach in systems biology. Many studies have generalized the outcomes to the different levels of central dogma information flow and assumed a correlation of transcript and protein expression levels. However, the relation between the various types of interaction (i.e., activation and inhibition) of gene products to their expression profiles has not been widely studied. In fact, looking for any perturbation according to differentially expressed genes is the common approach, while analyzing the effects of altered expression on the activity of signaling pathways is often ignored. In this study, we examine whether significant changes in gene expression necessarily lead to dysregulated signaling pathways. Using four commonly used and comprehensive databases, we extracted all relevant gene expression data and all relationships among directly linked gene pairs. We aimed to evaluate the ratio of coherency or sign consistency between the expression level as well as the causal relationships among the gene pairs. Through a comparison with random unconnected gene pairs, we illustrate that the signaling network is incoherent, and inconsistent with the recorded expression profile. Finally, we demonstrate that, to infer perturbed signaling pathways, we need to consider the type of relationships in addition to gene-product expression data, especially at the transcript level. We assert that identifying enriched biological processes via differentially expressed genes is limited when attempting to infer dysregulated pathways.Peer reviewe

Little genetic differentiation as assessed by uniparental markers in the presence of substantial language variation in peoples of the Cross River region of Nigeria

<p>Abstract</p> <p>Background</p> <p>The Cross River region in Nigeria is an extremely diverse area linguistically with over 60 distinct languages still spoken today. It is also a region of great historical importance, being a) adjacent to the likely homeland from which Bantu-speaking people migrated across most of sub-Saharan Africa 3000-5000 years ago and b) the location of Calabar, one of the largest centres during the Atlantic slave trade. Over 1000 DNA samples from 24 clans representing speakers of the six most prominent languages in the region were collected and typed for Y-chromosome (SNPs and microsatellites) and mtDNA markers (Hypervariable Segment 1) in order to examine whether there has been substantial gene flow between groups speaking different languages in the region. In addition the Cross River region was analysed in the context of a larger geographical scale by comparison to bordering Igbo speaking groups as well as neighbouring Cameroon populations and more distant Ghanaian communities.</p> <p>Results</p> <p>The Cross River region was shown to be extremely homogenous for both Y-chromosome and mtDNA markers with language spoken having no noticeable effect on the genetic structure of the region, consistent with estimates of inter-language gene flow of 10% per generation based on sociological data. However the groups in the region could clearly be differentiated from others in Cameroon and Ghana (and to a lesser extent Igbo populations). Significant correlations between genetic distance and both geographic and linguistic distance were observed at this larger scale.</p> <p>Conclusions</p> <p>Previous studies have found significant correlations between genetic variation and language in Africa over large geographic distances, often across language families. However the broad sampling strategies of these datasets have limited their utility for understanding the relationship within language families. This is the first study to show that at very fine geographic/linguistic scales language differences can be maintained in the presence of substantial gene flow over an extended period of time and demonstrates the value of dense sampling strategies and having DNA of known and detailed provenance, a practice that is generally rare when investigating sub-Saharan African demographic processes using genetic data.</p

MGP Panel is a comprehensive targeted genomics panel for molecular profiling of multiple myeloma patients

PURPOSE: We designed a comprehensive multiple myeloma (MM) targeted sequencing panel to identify common genomic abnormalities in a single assay and validated it against known standards. EXPERIMENTAL DESIGN: The panel comprised 228 genes/exons for mutations, 6 regions for translocations, and 56 regions for copy number abnormalities (CNAs). Toward panel validation, targeted sequencing was conducted on 233 patient samples and further validated using clinical fluorescence in situ hybridization (FISH) (translocations), multiplex ligation probe analysis (MLPA) (CNAs), whole genome sequencing (WGS) (CNAs, mutations, translocations) or droplet digital PCR (ddPCR) of known standards (mutations). RESULTS: Canonical IgH translocations were detected in 43.2% of patients by sequencing, and aligned with FISH except for one patient. CNAs determined by sequencing and MLPA for 22 regions were comparable in 103 samples and concordance between platforms was R2=0.969. VAFs for 74 mutations were compared between sequencing and ddPCR with concordance of R2=0.9849. CONCLUSIONS: In summary, we have developed a targeted sequencing panel that is as robust or superior to FISH and WGS. This molecular panel is cost effective, comprehensive, clinically actionable and can be routinely deployed to assist risk stratification at diagnosis or post-treatment to guide sequencing of therapies

Genetic legacy of state centralization in the Kuba Kingdom of the Democratic Republic of the Congo

Few phenomena have had as profound or long-lasting consequences in human history as the emergence of large-scale centralized states in the place of smaller scale and more local societies. This study examines a fundamental, and yet unexplored, consequence of state formation: its genetic legacy. We studied the genetic impact of state centralization during the formation of the eminent precolonial Kuba Kingdom of the Democratic Republic of the Congo (DRC) in the 17th century. We analyzed genome-wide data from over 690 individuals sampled from 27 different ethnic groups from the Kasai Central Province of the DRC. By comparing genetic patterns in the present-day Kuba, whose ancestors were part of the Kuba Kingdom, with those in neighboring non-Kuba groups, we show that the Kuba today are more genetically diverse and more similar to other groups in the region than expected, consistent with the historical unification of distinct subgroups during state centralization. We also found evidence of genetic mixing dating to the time of the Kingdom at its most prominent. Using this unique dataset, we characterize the genetic history of the Kasai Central Province and describe the historic late wave of migrations into the region that contributed to a Bantu-like ancestry component found across large parts of Africa today. Taken together, we show the power of genetics to evidence events of sociopolitical importance and highlight how DNA can be used to better understand the behaviors of both people and institutions in the past

Whole-genome analysis of Nigerian patients with breast cancer reveals ethnic-driven somatic evolution and distinct genomic subtypes

Black women across the African diaspora experience more aggressive breast cancer with higher mortality rates than white women of European ancestry. Although inter-ethnic germline variation is known, differential somatic evolution has not been investigated in detail. Analysis of deep whole genomes of 97 breast cancers, with RNA-seq in a subset, from women in Nigeria in comparison with The Cancer Genome Atlas (n = 76) reveal a higher rate of genomic instability and increased intra-tumoral heterogeneity as well as a unique genomic subtype defined by early clonal GATA3 mutations with a 10.5-year younger age at diagnosis. We also find non-coding mutations in bona fide drivers (ZNF217 and SYPL1) and a previously unreported INDEL signature strongly associated with African ancestry proportion, underscoring the need to expand inclusion of diverse populations in biomedical research. Finally, we demonstrate that characterizing tumors for homologous recombination deficiency has significant clinical relevance in stratifying patients for potentially life-saving therapies

Multi-site clonality analysis uncovers pervasive heterogeneity across melanoma metastases

Abstract: Metastatic melanoma carries a poor prognosis despite modern systemic therapies. Understanding the evolution of the disease could help inform patient management. Through whole-genome sequencing of 13 melanoma metastases sampled at autopsy from a treatment naïve patient and by leveraging the analytical power of multi-sample analyses, we reveal evidence of diversification among metastatic lineages. UV-induced mutations dominate the trunk, whereas APOBEC-associated mutations are found in the branches of the evolutionary tree. Multi-sample analyses from a further seven patients confirmed that lineage diversification was pervasive, representing an important mode of melanoma dissemination. Our analyses demonstrate that joint analysis of cancer cell fraction estimates across multiple metastases can uncover previously unrecognised levels of tumour heterogeneity and highlight the limitations of inferring heterogeneity from a single biopsy

Multi-site clonality analysis uncovers pervasive heterogeneity across melanoma metastases

From Springer Nature via Jisc Publications RouterHistory: received 2019-11-18, accepted 2020-07-27, registration 2020-08-04, pub-electronic 2020-08-27, online 2020-08-27, collection 2020-12Publication status: PublishedAbstract: Metastatic melanoma carries a poor prognosis despite modern systemic therapies. Understanding the evolution of the disease could help inform patient management. Through whole-genome sequencing of 13 melanoma metastases sampled at autopsy from a treatment naïve patient and by leveraging the analytical power of multi-sample analyses, we reveal evidence of diversification among metastatic lineages. UV-induced mutations dominate the trunk, whereas APOBEC-associated mutations are found in the branches of the evolutionary tree. Multi-sample analyses from a further seven patients confirmed that lineage diversification was pervasive, representing an important mode of melanoma dissemination. Our analyses demonstrate that joint analysis of cancer cell fraction estimates across multiple metastases can uncover previously unrecognised levels of tumour heterogeneity and highlight the limitations of inferring heterogeneity from a single biopsy

Whole-genome analysis of Nigerian patients with breast cancer reveals ethnic-driven somatic evolution and distinct genomic subtypes

From Springer Nature via Jisc Publications RouterHistory: received 2020-12-12, accepted 2021-11-02, registration 2021-11-04, pub-electronic 2021-11-26, online 2021-11-26, collection 2021-12Publication status: PublishedFunder: Postdoctoral Research Fellowship P2BSP3_178591Funder: Francis Crick Institute (Francis Crick Institute Limited); doi: https://doi.org/10.13039/100010438Funder: Cancer Research UK (CRUK); doi: https://doi.org/10.13039/501100000289; Grant(s): FC001202Funder: Wellcome Trust (Wellcome); doi: https://doi.org/10.13039/100004440; Grant(s): FC001202Funder: U.S. Department of Health & Human Services | National Institutes of Health (NIH); doi: https://doi.org/10.13039/100000002; Grant(s): U01 CA161032, U01 CA161032, R01 MD013452, R01 CA228198, U01 CA161032, R01 MD013452, P20-CA233307Funder: U.S. Department of Health & Human Services | National Institutes of Health (NIH)Funder: Breast Cancer Research Foundation (BCRF); doi: https://doi.org/10.13039/100001006; Grant(s): BCRF-20-071, BCRF-19-120Funder: DH | National Institute for Health Research (NIHR); doi: https://doi.org/10.13039/501100000272; Grant(s): 203141/Z/16/ZFunder: Susan G. Komen (Susan G. Komen Breast Cancer Foundation); doi: https://doi.org/10.13039/100009634; Grant(s): SAC110026, SAC210203Funder: American Cancer Society (American Cancer Society, Inc.); doi: https://doi.org/10.13039/100000048Abstract: Black women across the African diaspora experience more aggressive breast cancer with higher mortality rates than white women of European ancestry. Although inter-ethnic germline variation is known, differential somatic evolution has not been investigated in detail. Analysis of deep whole genomes of 97 breast cancers, with RNA-seq in a subset, from women in Nigeria in comparison with The Cancer Genome Atlas (n = 76) reveal a higher rate of genomic instability and increased intra-tumoral heterogeneity as well as a unique genomic subtype defined by early clonal GATA3 mutations with a 10.5-year younger age at diagnosis. We also find non-coding mutations in bona fide drivers (ZNF217 and SYPL1) and a previously unreported INDEL signature strongly associated with African ancestry proportion, underscoring the need to expand inclusion of diverse populations in biomedical research. Finally, we demonstrate that characterizing tumors for homologous recombination deficiency has significant clinical relevance in stratifying patients for potentially life-saving therapies

The Essentiality of Reporting Hardy-Weinberg Equilibrium Calculations in Population-Based Genetic Association Studies

Population-based genetic association studies have proven to be a powerful tool in identifying genes implicated in many complex human diseases that have a huge impact on public health. An essential quality control step in such studies is to undertake Hardy-Weinberg equilibrium (HWE) calculations. Deviations from HWE in the control group may reflect important problems including selection bias, population stratification and genotyping errors. If HWE is violated, the inferences of these studies may thus be biased. We therefore aimed to examine the extent to which HWE calculations are reported in genetic association studies published in Cell Journal(Yakhteh) (Cell J). Using keywords pertaining to genetic association studies, eleven relevant articles were identified of which ten provided full genotypic data. The genotype distribution of 16 single nucleotide polymorphisms (SNPs) was re-analyzed for HWE by using three different methods where appropriate. HWE was not reported in 60% of all articles investigated. Among those reporting, only one article provided calculations correctly and in detail. Therefore, 90% of articles analyzed failed to provide sufficient HWE data. Interestingly, three articles had significant HWE deviation in their control groups of which one highly deviated from HWE expectations (P= 9.8×10-12). We thus show that HWE calculations are under-reported in genetic association studies published in this journal. Furthermore, the conclusions of the three studies showing significant HWE in their control groups should be treated cautiously as they may be potentially misleading. We therefore recommend that reporting of detailed HWE calculations should become mandatory for such studies in the future