Analysis Of Individual Genomes Research Articles

Precision Medicine: An Emerging Approach for Patient Care

The philosophy behind contemporary healthcare is that one size fits all. Unfortunately, the outcomes of a standardized treatment regimen are not always uniform. That’s where the concept of precision medicine comes in. According to the Precision Medicine Initiative, precision medicine is “an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person.” This approach allow doctors and researchers to predict more accurately which treatment and prevention strategies for a particular disease will work in which groups of people and is in contrast to a one-size-fits-all approach, in which disease treatment and prevention strategies are developed for the average person, with less consideration for the differences between individuals. Although the term “precision medicine” is relatively new, the concept has been a part of healthcare for many years. For example, a person who needs a blood transfusion is not given blood from a randomly selected donor; instead, the donor’s blood type is matched to the recipient to reduce the risk of complications. The adoption of precision medicine will grow because its benefits to healthcare providers and patients are numerous. The highlighting ones are to shift the emphasis in medicine from reaction to prevention, predict susceptibility to disease, improve disease detection, preempt disease progression, customize disease-prevention strategies, prescribe more effective drugs, avoid prescribing drugs with predictable side effects and so on.The goal of precision medicine is to target the right treatments to the right patients at the right time. The short-term goals involve expanding precision medicine in the area of cancer research. Researchers at the National Cancer Institute (NCI) hope to use an increased knowledge of the genetics and biology of cancer to find new, more effective treatments for various forms of this disease. The long-term goals of the Precision Medicine Initiative focus on bringing precision medicine to all areas of health and healthcare on a large scale. Insufficient technologies, limited knowledge, and gaps in research are major obstacles to adding precision medicine to routine clinical care. Advances in precision medicine have already led to powerful new discoveries and FDA-approved treatments that are tailored to specific characteristics of individuals. Patients with a variety of cancers routinely undergo molecular testing as part of patient care, enabling physicians to select treatments that improve chances of survival and reduce exposure to adverse effects. Precision medicine will timely enable clinicians to integrate healthcare data with targeted assays and tests to identify and assess disease biomarkers and risks, determine actionable genetic variants in patients, obtain the entire picture of the metabolome, and map metabolites to disease pathways. Implementof precision medicine as a holistic approach, requires integration of genetic, genomic, clinical, environmental and life-style data using mechanistic models that are complex, and must be built from the ground up. The scientific approach would be to perform analysis of individual genomes giving rise to a new form of preventive and personalised medicine in healthcare. Availability of gene-based designer drugs, precise targeting of molecular fingerprints for disease, appropriate drug therapy, predicting individual susceptibility to disease, diagnosis, and treatment of illness are all a few of the many transformations expected in the decade to come. Bangladesh J Medicine 2023; Vol. 34, No. 2(1) Supplement: 201

QTeller: a tool for comparative multi-genomic gene expression analysis.

Over the last decade, RNA-Seq whole-genome sequencing has become a widely used method for measuring and understanding transcriptome-level changes in gene expression. Since RNA-Seq is relatively inexpensive, it can be used on multiple genomes to evaluate gene expression across many different conditions, tissues and cell types. Although many tools exist to map and compare RNA-Seq at the genomics level, few web-based tools are dedicated to making data generated for individual genomic analysis accessible and reusable at a gene-level scale for comparative analysis between genes, across different genomes and meta-analyses. To address this challenge, we revamped the comparative gene expression tool qTeller to take advantage of the growing number of public RNA-Seq datasets. qTeller allows users to evaluate gene expression data in a defined genomic interval and also perform two-gene comparisons across multiple user-chosen tissues. Though previously unpublished, qTeller has been cited extensively in the scientific literature, demonstrating its importance to researchers. Our new version of qTeller now supports multiple genomes for intergenomic comparisons, and includes capabilities for both mRNA and protein abundance datasets. Other new features include support for additional data formats, modernized interface and back-end database and an optimized framework for adoption by other organisms' databases. The source code for qTeller is open-source and available through GitHub (https://github.com/Maize-Genetics-and-Genomics-Database/qTeller). A maize instance of qTeller is available at the Maize Genetics and Genomics database (MaizeGDB) (https://qteller.maizegdb.org/), where we have mapped over 200 unique datasets from GenBank across 27 maize genomes. Supplementary data are available at Bioinformatics online.

Genetics and Genomics of Breast Cancer: update and translational perspectives.

In the recent years the rapid scientific innovation in the evaluation of the individual's genome have allowed the identification of variants associated with the onset, treatment and prognosis of various pathologies including cancer, and with a potential impact in the assessment of therapy responses. Despite the analysis and interpretation of genomic information is considered incomplete, in many cases the identification of specific genomic profile has allowed the stratification of subgroups of patients characterized by a better response to drug therapies. Individual genome analysis has changed profoundly the diagnostic and therapeutic approach of breast cancer in the last 15 years by identifying selective molecular lesions that drive the development of neoplasms, showing that each tumor has its own genomic signature, with some specific features and some features common to several sub-types. Several personalized therapies have been (and still are being) developed showing a remarkable efficacy in the treatment of breast cancer.

Genomic Analysis of the Human Gut Microbiome Suggests Novel Enzymes Involved in Quinone Biosynthesis.

Ubiquinone and menaquinone are membrane lipid-soluble carriers of electrons that are essential for cellular respiration. Eukaryotic cells can synthesize ubiquinone but not menaquinone, whereas prokaryotes can synthesize both quinones. So far, most of the human gut microbiome (HGM) studies have been based on metagenomic analysis. Here, we applied an analysis of individual HGM genomes to the identification of ubiquinone and menaquinone biosynthetic pathways. In our opinion, the shift from metagenomics to analysis of individual genomes is a pivotal milestone in investigation of bacterial communities, including the HGM. The key results of this study are as follows. (i) The distribution of the canonical pathways in the HGM genomes was consistent with previous reports and with the distribution of the quinone-dependent reductases for electron acceptors. (ii) The comparative genomics analysis identified four alternative forms of the previously known enzymes for quinone biosynthesis. (iii) Genes for the previously unknown part of the futalosine pathway were identified, and the corresponding biochemical reactions were proposed. We discuss the remaining gaps in the menaquinone and ubiquinone pathways in some of the microbes, which indicate the existence of further alternate genes or routes. Together, these findings provide further insight into the biosynthesis of quinones in bacteria and the physiology of the HGM.

Identification of copy number variants in whole-genome data using Reference Coverage Profiles.

The identification of DNA copy numbers from short-read sequencing data remains a challenge for both technical and algorithmic reasons. The raw data for these analyses are measured in tens to hundreds of gigabytes per genome; transmitting, storing, and analyzing such large files is cumbersome, particularly for methods that analyze several samples simultaneously. We developed a very efficient representation of depth of coverage (150–1000× compression) that enables such analyses. Current methods for analyzing variants in whole-genome sequencing (WGS) data frequently miss copy number variants (CNVs), particularly hemizygous deletions in the 1–100 kb range. To fill this gap, we developed a method to identify CNVs in individual genomes, based on comparison to joint profiles pre-computed from a large set of genomes. We analyzed depth of coverage in over 6000 high quality (>40×) genomes. The depth of coverage has strong sequence-specific fluctuations only partially explained by global parameters like %GC. To account for these fluctuations, we constructed multi-genome profiles representing the observed or inferred diploid depth of coverage at each position along the genome. These Reference Coverage Profiles (RCPs) take into account the diverse technologies and pipeline versions used. Normalization of the scaled coverage to the RCP followed by hidden Markov model (HMM) segmentation enables efficient detection of CNVs and large deletions in individual genomes. Use of pre-computed multi-genome coverage profiles improves our ability to analyze each individual genome. We make available RCPs and tools for performing these analyses on personal genomes. We expect the increased sensitivity and specificity for individual genome analysis to be critical for achieving clinical-grade genome interpretation.

Lo SM, Choi M, Liu J, et al. Phenotype diversity in type 1 Gaucher disease: discovering the genetic basis of Gaucher disease/hematologic malignancy phenotype by individual genome analysis. Blood. 2012;119(20):

Lo SM, Choi M, Liu J, et al. Phenotype diversity in type 1 Gaucher disease: discovering the genetic basis of Gaucher disease/hematologic malignancy phenotype by individual genome analysis. Blood. 2012;119(20):

Personalization of targeted therapy in advanced thyroid cancer.

Although generally the prognosis of differentiated thyroid carcinoma (DTC) is good, approximately 5% of people are likely to develop metastases which fail to respond to radioactive iodine, and other traditional therapies, exhibiting a more aggressive behavior. Nowadays, therapy is chosen and implemented on a watch-and-wait basis for most DTC patients. Which regimen is likely to work best is decided on the basis of an individual’s clinical information, but only data referring to outcomes of groups of patients are employed. To predict the best course of therapy, an individual patient’s biologic data is rarely employed in a systematic way. Anyway, the use of not expensive individual genomic analysis could lead us to a new era of patient-specific and personalized care. Recently, key targets that are now being evaluated in the clinical setting have been evidenced in the pathogenesis of these diseases. Some of the known genetic alterations playing a crucial role in the development of thyroid cancer include B-Raf gene mutations, rearranged during transfection/ papillary thyroid carcinoma gene rearrangements, and vascular endothelial growth factor receptor-2 angiogenesis pathways. The development of targeted novel compounds able to induce clinical responses and stabilization of disease has overcome the lack of effective therapies for DTC, which are resistant to radioiodine and thyroid stimulating hormone-suppressive therapy. Interestingly, the best responses have been demonstrated in patients treated with anti-angiogenic inhibitors such as vandetanib and XL184 in medullary thyroid cancer, and sorafenib in papillary and follicular DTC.

"Molecular profiling and ways towards personalized medicine in advanced differentiated thyroid cancer".

The increasing incidence of thyroid nodules and cancer is associated with a higher demand for the diagnosis of thyroid nod-ules, and the treatment of this aggressive disease. Molecular biology in the last decades has given important contributions in the understanding of the pathogenesis of thyroid cancer, and it is successfully used for the diagnosis of thyroid nodules. An important diagnostic impact can be achieved by testing fine needle aspiration samples, from thyroid nodules, for a panel of mutations that typically includes BRAF, RAS, RET/PTC, and PAX8/PPARg. The use of these and other emerging molecular markers is expected to improve significantly the accuracy of cancer diagnosis in thyroid nodules, overall in those with undeterminate cytology (Thyr 3). With this aim many researches evaluated (by new promising techniques) proteomics, and metabolomics of fine needle aspiration. Mortality rates from thyroid cancer mainly depend on its aggressiveness. Geno- and pheno-typing of aggressive thyroid cancer has advanced our understanding of treatment failures and of potential future therapies. Unraveling molecular signaling pathways of thyroid cancer including its aggressive forms will hopefully pave the road to reduce mortality but also morbidity from this cancer. Reliable pre-operative identification of high-risk patients may productively guide the initial surgical management since re-operative neck surgery is associated with increased morbidity. Pre-operative knowledge of mutations typically associated with thyroid cancer could alter the initial surgical treatment for at least 20% of patients and can potentially prevent the increased morbidity associated with reoperative neck exploration. Despite the generally good prognosis of differentiated thyroid carcinoma (DTC), about 5% of patients will develop metastases which fail to respond to radioactive iodine (RaI), and other traditional therapies, exhibiting a more aggressive behavior. The advent of low-cost individual genomic analysis provides hope that we are entering a new era of personalized, patient-specific care. The recent advances in the pathogenesis of these diseases have revealed key targets (BRAF, RAS, RET, VEGFR, EGFR, etc.) that are now being evaluated in the clinical setting. The lack of effective therapies for DTC, resistant to radioiodine and traditional therapies, is now being overcome by the development of targeted novel compounds that have been demonstrated to induce clinical responses and stabilization of the disease. Interestingly, the most promising responses have been reported in patients treated with antiangiogenic inhibitors such as vandetanib and XL184 in medullary thyroid cancer, and sorafenib in papillary and follicular DTC. However, the increasing complexity of the diagnostic and therapeutic tools for thyroid cancer needs, more and more, effort to personalize the diagnosis and the treatment, to reach the maximum success, avoiding unnecessary and potentially harmful treatments. The aim of this Mini-Thematic Issue was to present and to discuss the most recent advancements to personalize the diagnosis and the treatment of thyroid nodules and cancer.

RhodopsinF45L Allele Does Not Cause Autosomal Dominant Retinitis Pigmentosa in a Large Caucasian Family

To ascertain the potential pathogenicity of a retinitis pigmentosa (RP)-causing RHO F45L allele in a family affected by congenital achromatopsia (ACHM). Case series/observational study that included two patients with ACHM and 24 extended family members. Molecular genetic analysis was performed to identify RHO F45L carrier status in the family and a control population. An adaptive optics scanning light ophthalmoscope (AOSLO) was used to image the photoreceptor mosaic and assess rod and cone structure. Spectral domain optical coherence tomography (SD-OCT) was used to examine retinal lamination. Comprehensive clinical testing included acuity, color vision, and dilated fundus examination. Electroretinography was used to assess rod and cone function. Five carriers of the RHO F45L allele alone (24-80 years) and three carriers in combination with a heterozygous CNGA3 mutant allele (10-64 years) were all free of the classic symptoms and signs of RP. In heterozygous carriers of both mutations, SD-OCT showed normal retinal thickness and intact outer retinal layers; rod and cone densities were within normal limits on AOSLO. The phenotype in two individuals affected with ACHM and harboring the RHO F45L allele was indistinguishable from that previously reported for ACHM. The RHO F45L allele is not pathogenic in this large family; hence, the two ACHM patients would unlikely develop RP in the future. The combined approach of comprehensive molecular analysis of individual genomes and noninvasive cellular resolution retinal imaging enhances the current repertoire of clinical diagnostic tools, giving a substantial impetus to personalized medicine.

Phenotype diversity in type 1 Gaucher disease: discovering the genetic basis of Gaucher disease/hematologic malignancy phenotype by individual genome analysis

AbstractGaucher disease (GD), an inherited macrophage glycosphingolipidosis, manifests with an extraordinary variety of phenotypes that show imperfect correlation with mutations in the GBA gene. In addition to the classic manifestations, patients suffer from increased susceptibility to hematologic and nonhematologic malignancies. The mechanism(s) underlying malignancy in GD is not known, but is postulated to be secondary to macrophage dysfunction and immune dysregulation arising from lysosomal accumulation of glucocerebroside. However, there is weak correlation between GD/cancer phenotype and the systemic burden of glucocerebroside-laden macrophages. Therefore, we hypothesized that genetic modifier(s) may underlie the GD/cancer phenotype. In the present study, the genetic basis of GD/T-cell acute lymphoblastic lymphoma in 2 affected siblings was deciphered through genomic analysis. GBA gene sequencing revealed homozygosity for a novel mutation, D137N. Whole-exome capture and massively parallel sequencing combined with homozygosity mapping identified a homozygous novel mutation in the MSH6 gene that leads to constitutional mismatch repair deficiency syndrome and increased cancer risk. Enzyme studies demonstrated that the D137N mutation in GBA is a pathogenic mutation, and immunohistochemistry confirmed the absence of the MSH6 protein. Therefore, precise phenotype annotation followed by individual genome analysis has the potential to identify genetic modifiers of GD, facilitate personalized management, and provide novel insights into disease pathophysiology.

Increased complexity of gene structure and base composition in vertebrates

How the structure and base composition of genes changed with the evolution of vertebrates remains a puzzling question. Here we analyzed 895 orthologous protein-coding genes in six multicellular animals: human, chicken, zebrafish, sea squirt, fruit fly, and worm. Our analyses reveal that many gene regions, particularly intron and 3' UTR, gradually expanded throughout the evolution of vertebrates from their invertebrate ancestors, and that the number of exons per gene increased. Studies based on all protein-coding genes in each genome provide consistent results. We also find that GC-content increased in many gene regions (especially 5' UTR) in the evolution of endotherms, except in coding-exons. Analysis of individual genomes shows that 3' UTR demonstrated stronger length and GC-content correlation with intron than 5' UTR, and gene with large intron in all six species demonstrated relatively similar GC-content. Our data indicates a great increase in complexity in vertebrate genes and we propose that the requirement for morphological and functional changes is probably the driving force behind the evolution of structure and base composition complexity in multicellular animal genes.

Obesity: from animal models to human genetics to practical applications.

Although many animal models are used in genetic studies, the mouse is most common. Analysis of single-gene mutations, linkage analysis in crossbred strains, and gene targeting are the primary techniques used to associate obesity phenotypes with specific genes or alleles. The orthologous human gene can then be tested, either in linkage studies in families or in genome-wide association studies (GWAS), for effect on the phenotype. Frequent lack of concordance between mouse and human obesity genes may be due to the difference in phenotypes measured in humans (body mass index) versus mouse (fat mass or % body fat), lack of intermediate phenotypes, and the fact that identified genes account for only a small percentage of the heritability of common obesity, suggesting that many genes remain unknown. New technology allows analysis of individual genomes at a reasonable cost, making large-scale obesity genome projects in humans feasible. Such projects could identify common allelic variants that contribute to obesity and to variable individual response to obesity therapy. Currently, family history may be more predictive than genetics for risk of obesity, but individual testing could ultimately guide therapy and, in the aggregate, guide public health policy. The primary limitation to development of genotype-based diets is that successful randomized diet trials of widely ranging macronutrient content, adequately powered for finding rare Mendelian mutations, have not been performed.

Unraveling the thrombophilia paradox: from hypercoagulability to the prothrombotic state.

The thrombophilia paradox whereby thrombophilia testing identifies defects associated with an increased risk of a first venous thrombosis but not of a particularly high risk of recurrence is likely the result of limitations imposed by a limited dichotomous testing strategy compounded by test inaccuracy and imprecision. Consequently, the observed intermediate phenotype (defined by limited laboratory test results) is not fully concordant with the heritable genotype. The next generation of thrombophilia tests, which utilize either individual genomic analysis or global measurement of the composite plasma intermediate phenotype, may more accurately quantify the thrombophilic risk. In conjunction with clinical risk assessment a more quantitative measurement of hypercoagulability and definition of the prothrombotic state should facilitate transition of clinical management from a disease-focused to a more patient-focused strategy.

Public interest and expectations concerning commercial genotyping and genetic risk assessment.

In contrast to the modest progress made in the interpretation and clinical application of genomic data, genotyping technologies have experienced great progress. Genotyping costs are progressively decreasing making individual genotyping more commonly available. Financial availability of individual genome analysis and the strong desire of many people to know about their individual genomic characteristics, promotes the marketing of genetic tests of variable predictive value directly to the public. A survey of 2000 Russian respondents revealed very positive attitudes and beliefs towards these genetic developments: 85% of surveyed individuals would like to have their genetic risk for avoidable diseases estimated, and 89% responded stating that they would try to change their lifestyle by giving up bad habits, following a recommended diet or taking medications if a high risk of disease was identified. It is believed that with time, validated genetic information will find its rightful place in medicine, by supplementing phenotypic clinical data with validated genetic interpretations.

On the origin of microbial ORFans: quantifying the strength of the evidence for viral lateral transfer

Background:The origin of microbial ORFans, ORFs having no detectable homology to other ORFs in the databases, is one of the unexplained puzzles of the post-genomic era. Several hypothesis on the origin of ORFans have been suggested in the last few years, most of which based on selected, relatively small, subsets of ORFans. One of the hypotheses for the origin of ORFans is that they have been acquired thru lateral transfer from viruses. Here we carry out a comprehensive, genome-wide study on the origins of ORFans to quantify the strength of current evidence supporting this hypothesis.Results:We performed similarity searches by querying all current ORFans against the public virus protein database. Surprisingly, we found that only 2.8% of all microbial ORFans have detectable homologs in viruses, while the percentage of non-ORFans with detectable homologs in viruses is 7.9%, a significantly higher figure. This suggests that the current evidence for the origin of ORFans from lateral transfer from viruses is at best weak. However, an analysis of individual genomes revealed a number of organisms with much higher percentages, many of them belonging to the Firmicutes and Gamma-proteobacteria. We provide evidence suggesting that the current virus database may be biased towards those viruses attacking Firmicutes and Gamma-proteobacteria.Conclusion:We conclude that as more viral genomes are sequenced, more microbial ORFans will find homologs in viruses, but this trend may vary much for individual genomes. Thus, lateral transfer from viruses alone is unlikely to explain the origin of the majority of ORFans in the majority of prokaryotes and consequently, other, not necessarily exclusive, mechanisms are likely to better explain the origin of the increasing number of ORFans.

Toward the $1000 Human Genome

Revolutionary new technologies, capable of transforming the economics of sequencing, are providing an unparalleled opportunity to analyze human genetic variation comprehensively at the whole-genome level within a realistic timeframe and at affordable costs. Current estimates suggest that it would cost somewhere in the region of 30 million US dollars to sequence an entire human genome using Sanger-based sequencing, and on one machine it would take about 60 years. Solexa is widely regarded as a company with the necessary disruptive technology to be the first to achieve the ultimate goal of the so-called 1,000 dollars human genome - the conceptual cost-point needed for routine analysis of individual genomes. Solexa's technology is based on completely novel sequencing chemistry capable of sequencing billions of individual DNA molecules simultaneously, a base at a time, to enable highly accurate, low cost analysis of an entire human genome in a single experiment. When applied over a large enough genomic region, these new approaches to resequencing will enable the simultaneous detection and typing of known, as well as unknown, polymorphisms, and will also offer information about patterns of linkage disequilibrium in the population being studied. Technological progress, leading to the advent of single-molecule-based approaches, is beginning to dramatically drive down costs and increase throughput to unprecedented levels, each being several orders of magnitude better than that which is currently available. A new sequencing paradigm based on single molecules will be faster, cheaper and more sensitive, and will permit routine analysis at the whole-genome level.