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Changes in the composition of the microbiome over time are associated with myriad human illnesses. Unfortunately, the lack of analytic techniques has hindered researchers' ability to quantify the association between longitudinal microbial composition and time-to-event outcomes. Prior methodological work developed the joint model for longitudinal and time-to-event data to incorporate time-dependent biomarker covariates into the hazard regression approach to disease outcomes. The original implementation of this joint modeling approach employed a linear mixed effects model to represent the time-dependent covariates. However, when the distribution of the time-dependent covariate is non-Gaussian, as is the case with microbial abundances, researchers require different statistical methodology. We present a joint modeling framework that uses a negative binomial mixed effects model to determine longitudinal taxon abundances. We incorporate these modeled microbial abundances into a hazard function with a parameterization that not only accounts for the proportional nature of microbiome data, but also generates biologically interpretable results. Herein we demonstrate the performance improvements of our approach over existing alternatives via simulation as well as a previously published longitudinal dataset studying the microbiome during pregnancy. The results demonstrate that our joint modeling framework for longitudinal microbiome count data provides a powerful methodology to uncover associations between changes in microbial abundances over time and the onset of disease. This method offers the potential to equip researchers with a deeper understanding of the associations between longitudinal microbial composition changes and disease outcomes. This new approach could potentially lead to new diagnostic biomarkers or inform clinical interventions to help prevent or treat disease.

NGS studies have uncovered an ever-growing catalog of human variation while leaving an enormous gap between observed variation and experimental characterization of variant function. High-throughput screens powered by NGS have greatly increased the rate of variant functionalization, but the development of comprehensive statistical methods to analyze screen data has lagged. In the massively parallel reporter assay (MPRA), short barcodes are counted by sequencing DNA libraries transfected into cells and the cell's output RNA in order to simultaneously measure the shifts in transcription induced by thousands of genetic variants. These counts present many statistical challenges, including overdispersion, depth dependence, and uncertain DNA concentrations. So far, the statistical methods used have been rudimentary, employing transformations on count level data and disregarding experimental and technical structure while failing to quantify uncertainty in the statistical model. We have developed an extensive framework for the analysis of NGS functionalization screens available as an R package called malacoda (available from github.com/andrewGhazi/malacoda). Our software implements a probabilistic, fully Bayesian model of screen data. The model uses the negative binomial distribution with gamma priors to model sequencing counts while accounting for effects from input library preparation and sequencing depth. The method leverages the high-throughput nature of the assay to estimate the priors empirically. External annotations such as ENCODE data or DeepSea predictions can also be incorporated to obtain more informative priors-a transformative capability for data integration. The package also includes quality control and utility functions, including automated barcode counting and visualization methods. To validate our method, we analyzed several datasets using malacoda and alternative MPRA analysis methods. These data include experiments from the literature, simulated assays, and primary MPRA data. We also used luciferase assays to experimentally validate several hits from our primary data, as well as variants for which the various methods disagree and variants detectable only with the aid of external annotations.

CD36 is a platelet membrane glycoprotein whose engagement with oxidized low-density lipoprotein (oxLDL) results in platelet activation. The CD36 gene has been associated with platelet count, platelet volume, as well as lipid levels and CVD risk by genome-wide association studies. Platelet CD36 expression levels have been shown to be associated with both the platelet oxLDL response and an elevated risk of thrombo-embolism. Several genomic variants have been identified as associated with platelet CD36 levels, however none have been conclusively demonstrated to be causative. We screened 81 expression quantitative trait loci (eQTL) single nucleotide polymorphisms (SNPs) associated with platelet CD36 expression by a Massively Parallel Reporter Assay (MPRA) and analyzed the results with a novel Bayesian statistical method. Ten eQTLs located 13kb to 55kb upstream of the CD36 transcriptional start site of transcript ENST00000309881 and 49kb to 92kb upstream of transcript ENST00000447544, demonstrated significant transcription shifts between their minor and major allele in the MPRA assay. Of these, rs2366739 and rs1194196, separated by only 20bp, were confirmed by luciferase assay to alter transcriptional regulation. In addition, electromobility shift assays demonstrated differential DNA:protein complex formation between the two alleles of this locus. Furthermore, deletion of the genomic locus by CRISPR/Cas9 in K562 and Meg-01 cells results in upregulation of CD36 transcription. These data indicate that we have identified a variant that regulates expression of CD36, which in turn affects platelet function. To assess the clinical relevance of our findings we used the PhenoScanner tool, which aggregates large scale GWAS findings; the results reinforce the clinical relevance of our variants and the utility of the MPRA assay. The study demonstrates a generalizable paradigm for functional testing of genetic variants to inform mechanistic studies, support patient management and develop precision therapies.

The fusion (F) protein of RSV is the major vaccine target. This protein undergoes a conformational change from pre-fusion to post-fusion. Both conformations share antigenic sites II and IV. Pre-fusion F has unique antigenic sites p27, ø, α2α3β3β4, and MPE8; whereas, post-fusion F has unique antigenic site I. Our objective was to determine the antigenic variability for RSV/A and RSV/B isolates from contemporary and historical genotypes compared to a historical RSV/A strain.The F sequences of isolates from GenBank, Houston, and Chile (N = 1,090) were used for this analysis. Sequences were compared pair-wise to a reference sequence, a historical RSV/A Long strain. Variability (calculated as %) was defined as changes at each amino acid (aa) position when compared to the reference sequence. Only aa at antigenic sites with variability ≥5% were reported.A total of 1,090 sequences (822 RSV/A and 268 RSV/B) were analyzed. When compared to the reference F, those domains with the greatest number of non-synonymous changes included the signal peptide, p27, heptad repeat domain 2, antigenic site ø, and the transmembrane domain. RSV/A subgroup had 7 aa changes in the antigenic sites: site I (N = 1), II (N = 1), p27 (N = 4), α2α3β3β4(AM14) (N = 1), ranging in frequency from 7-91%. In comparison, RSV/B had 19 aa changes in antigenic sites: I (N = 3), II (N = 1), p27 (N = 9), ø (N = 4), α2α3β3β4(AM14) (N = 1), and MPE8 (N = 1), ranging in frequency from 79-100%.Although antigenic sites of RSV F are generally well conserved, differences are observed when comparing the two subgroups to the reference RSV/A Long strain. Further, these discrepancies are accented in the antigenic sites in pre-fusion F of RSV/B isolates, often occurring with a frequency of 100%. This could be of importance if a monovalent F protein from the historical GA1 genotype of RSV/A is used for vaccine development.

[This corrects the article DOI: 10.1371/journal.pone.0175792.].

Automated in situ hybridization enables the construction of comprehensive atlases of gene expression patterns in mammals. Such atlases can become Web-searchable digital expression maps of individual genes and thus offer an entryway to elucidate genetic interactions and signaling pathways. Towards this end, an atlas housing approximately 1,000 spatial gene expression patterns of the midgestation mouse embryo was generated. Patterns were textually annotated using a controlled vocabulary comprising >90 anatomical features. Hierarchical clustering of annotations was carried out using distance scores calculated from the similarity between pairs of patterns across all anatomical structures. This process ordered hundreds of complex expression patterns into a matrix that reflects the embryonic architecture and the relatedness of patterns of expression. Clustering yielded 12 distinct groups of expression patterns. Because of the similarity of expression patterns within a group, members of each group may be components of regulatory cascades. We focused on the group containing Pax6, an evolutionary conserved transcriptional master mediator of development. Seventeen of the 82 genes in this group showed a change of expression in the developing neocortex of Pax6-deficient embryos. Electromobility shift assays were used to test for the presence of Pax6-paired domain binding sites. This led to the identification of 12 genes not previously known as potential targets of Pax6 regulation. These findings suggest that cluster analysis of annotated gene expression patterns obtained by automated in situ hybridization is a novel approach for identifying components of signaling cascades.

To better understand the systemic response to naturally acquired acute respiratory viral infections, we prospectively enrolled 1610 healthy adults in 2009 and 2010. Of these, 142 subjects were followed for detailed evaluation of acute viral respiratory illness. We examined peripheral blood gene expression at 7 timepoints: enrollment, 5 illness visits and the end of each year of the study. 133 completed all study visits and yielded technically adequate peripheral blood microarray gene expression data. Seventy-three (55%) had an influenza virus infection, 64 influenza A and 9 influenza B. The remaining subjects had a rhinovirus infection (N = 32), other viral infections (N = 4), or no viral agent identified (N = 24). The results, which were replicated between two seasons, showed a dramatic upregulation of interferon pathway and innate immunity genes. This persisted for 2-4 days. The data show a recovery phase at days 4 and 6 with differentially expressed transcripts implicated in cell proliferation and repair. By day 21 the gene expression pattern was indistinguishable from baseline (enrollment). Influenza virus infection induced a higher magnitude and longer duration of the shared expression signature of illness compared to the other viral infections. Using lineage and activation state-specific transcripts to produce cell composition scores, patterns of B and T lymphocyte depressions accompanied by a major activation of NK cells were detected in the acute phase of illness. The data also demonstrate multiple dynamic gene modules that are reorganized and strengthened following infection. Finally, we examined pre- and post-infection anti-influenza antibody titers defining novel gene expression correlates.

Blood microRNA (miRNA) levels have been associated with and shown to participate in disease pathophysiology. However, the hematopoietic cell of origin of blood miRNAs and the individual blood cell miRNA profiles are poorly understood. We report the miRNA content of highly purified normal hematopoietic cells from the same individuals. Although T-cells, B-cells and granulocytes had the highest miRNA content per cell, erythrocytes contributed more cellular miRNA to the blood, followed by granulocytes and platelets. miRNA profiling revealed different patterns and different expression levels of miRNA specific for each lineage. miR-30c-5p was determined to be an appropriate reference normalizer for cross-cell qRT-PCR comparisons. miRNA profiling of 5 hematopoietic cell lines revealed differential expression of miR-125a-5p. We demonstrated endogenous levels of miR-125a-5p regulate reporter gene expression in Meg-01 and Jurkat cells by (1) constructs containing binding sites for miR-125a-5p or (2) over-expressing or inhibiting miR-125a-5p. This quantitative analysis of the miRNA profiles of peripheral blood cells identifies the circulating hematopoietic cellular miRNAs, supports the use of miRNA profiles for distinguishing different hematopoietic lineages and suggests that endogenously expressed miRNAs can be exploited to regulate transgene expression in a cell-specific manner.

Human respiratory syncytial virus (HRSV) has three surface glycoproteins: small hydrophobic (SH), attachment (G) and fusion (F), encoded by three consecutive genes (SH-G-F). A 270-nt fragment of the G gene is used to genotype HRSV isolates. This study genotyped and investigated the variability of the gene and amino acid sequences of the three surface proteins of HRSV strains collected from 1987 to 2005 from one center. Sixty original clinical isolates and 5 prototype strains were analyzed. Sequences containing SH, F and G genes were generated, and multiple alignments and phylogenetic trees were analyzed. Genetic variability by protein domains comparing virus genotypes was assessed. Complete sequences of the SH-G-F genes were obtained for all 65 samples: HRSV-A = 35; HRSV-B = 30. In group A strains, genotypes GA5 and GA2 were predominant. For HRSV-B strains, the genotype GB4 was predominant from 1992 to 1994 and only genotype BA viruses were detected in 2004-2005. Different genetic variability at nucleotide level was detected between the genes, with G gene being the most variable and the highest variability detected in the 270-nt G fragment that is frequently used to genotype the virus. High variability (>10%) was also detected in the signal peptide and transmembrane domains of the F gene of HRSV A strains. Variability among the HRSV strains resulting in non-synonymous changes was detected in hypervariable domains of G protein, the signal peptide of the F protein, a not previously defined domain in the F protein, and the antigenic site Ø in the pre-fusion F. Divergent trends were observed between HRSV -A and -B groups for some functional domains. A diverse population of HRSV -A and -B genotypes circulated in Houston during an 18 year period. We hypothesize that diverse sequence variation of the surface protein genes provide HRSV strains a survival advantage in a partially immune-protected community.

Identification of the host genetic factors that contribute to variation in vaccine responsiveness may uncover important mechanisms affecting vaccine efficacy. We carried out an integrative, longitudinal study combining genetic, transcriptional, and immunologic data in humans given seasonal influenza vaccine. We identified 20 genes exhibiting a transcriptional response to vaccination, significant genotype effects on gene expression, and correlation between the transcriptional and antibody responses. The results show that variation at the level of genes involved in membrane trafficking and antigen processing significantly influences the human response to influenza vaccination. More broadly, we demonstrate that an integrative study design is an efficient alternative to existing methods for the identification of genes involved in complex traits.

Hematopoietic stem cells (HSCs) are rare quiescent cells that continuously replenish the cellular components of the peripheral blood. Observing that the ataxia-associated gene Ataxin-1-like (Atxn1L) was highly expressed in HSCs, we examined its role in HSC function through in vitro and in vivo assays. Mice lacking Atxn1L had greater numbers of HSCs that regenerated the blood more quickly than their wild-type counterparts. Molecular analyses indicated Atxn1L null HSCs had gene expression changes that regulate a program consistent with their higher level of proliferation, suggesting that Atxn1L is a novel regulator of HSC quiescence. To determine if additional brain-associated genes were candidates for hematologic regulation, we examined genes encoding proteins from autism- and ataxia-associated protein-protein interaction networks for their representation in hematopoietic cell populations. The interactomes were found to be highly enriched for proteins encoded by genes specifically expressed in HSCs relative to their differentiated progeny. Our data suggest a heretofore unappreciated similarity between regulatory modules in the brain and HSCs, offering a new strategy for novel gene discovery in both systems.

Curation and interpretation of copy number variants identified by genome-wide testing is challenged by the large number of events harbored in each personal genome. Conventional determination of phenotypic relevance relies on patterns of higher frequency in affected individuals versus controls; however, an increasing amount of ascertained variation is rare or private to clans. Consequently, frequency data have less utility to resolve pathogenic from benign. One solution is disease-specific algorithms that leverage gene knowledge together with variant frequency to aid prioritization. We used large-scale resources including Gene Ontology, protein-protein interactions and other annotation systems together with a broad set of 83 genes with known associations to epilepsy to construct a pathogenicity score for the phenotype. We evaluated the score for all annotated human genes and applied Bayesian methods to combine the derived pathogenicity score with frequency information from our diagnostic laboratory. Analysis determined Bayes factors and posterior distributions for each gene. We applied our method to subjects with abnormal chromosomal microarray results and confirmed epilepsy diagnoses gathered by electronic medical record review. Genes deleted in our subjects with epilepsy had significantly higher pathogenicity scores and Bayes factors compared to subjects referred for non-neurologic indications. We also applied our scores to identify a recently validated epilepsy gene in a complex genomic region and to reveal candidate genes for epilepsy. We propose a potential use in clinical decision support for our results in the context of genome-wide screening. Our approach demonstrates the utility of integrative data in medical genomics.

Disorders of sexual development (DSD), ranging in severity from genital abnormalities to complete sex reversal, are among the most common human birth defects with incidence rates reaching almost 3%. Although causative alterations in key genes controlling gonad development have been identified, the majority of DSD cases remain unexplained. To improve the diagnosis, we screened 116 children born with idiopathic DSD using a clinically validated array-based comparative genomic hybridization platform. 8951 controls without urogenital defects were used to compare with our cohort of affected patients. Clinically relevant imbalances were found in 21.5% of the analyzed patients. Most anomalies (74.2%) evaded detection by the routinely ordered karyotype and were scattered across the genome in gene-enriched subtelomeric loci. Among these defects, confirmed de novo duplication and deletion events were noted on 1p36.33, 9p24.3 and 19q12-q13.11 for ambiguous genitalia, 10p14 and Xq28 for cryptorchidism and 12p13 and 16p11.2 for hypospadias. These variants were significantly associated with genitourinary defects (P = 6.08×10(-12)). The causality of defects observed in 5p15.3, 9p24.3, 22q12.1 and Xq28 was supported by the presence of overlapping chromosomal rearrangements in several unrelated patients. In addition to known gonad determining genes including SRY and DMRT1, novel candidate genes such as FGFR2, KANK1, ADCY2 and ZEB2 were encompassed. The identification of risk germline rearrangements for urogenital birth defects may impact diagnosis and genetic counseling and contribute to the elucidation of the molecular mechanisms underlying the pathogenesis of human sexual development.

Spinocerebellar ataxia type 1 (SCA1) is a dominantly inherited neurodegenerative disease caused by expansion of a CAG repeat that encodes a polyglutamine tract in ATAXIN1 (ATXN1). Molecular and genetic data indicate that SCA1 is mainly caused by a gain-of-function mechanism. However, deletion of wild-type ATXN1 enhances SCA1 pathogenesis, whereas increased levels of an evolutionarily conserved paralog of ATXN1, Ataxin 1-Like, ameliorate it. These data suggest that a partial loss of ATXN1 function contributes to SCA1. To address this possibility, we set out to determine if the SCA1 disease model (Atxn1(154Q/+) mice) and the loss of Atxn1 function model (Atxn1-/- mice) share molecular changes that could potentially contribute to SCA1 pathogenesis. To identify transcriptional changes that might result from loss of function of ATXN1 in SCA1, we performed gene expression microarray studies on cerebellar RNA from Atxn1-/- and Atxn1(154Q/+) cerebella and uncovered shared gene expression changes. We further show that mild overexpression of Ataxin-1-Like rescues several of the molecular and behavioral defects in Atxn1-/- mice. These results support a model in which Ataxin 1-Like overexpression represses SCA1 pathogenesis by compensating for a partial loss of function of Atxn1. Altogether, these data provide evidence that partial loss of Atxn1 function contributes to SCA1 pathogenesis and raise the possibility that loss-of-function mechanisms contribute to other dominantly inherited neurodegenerative diseases.

MicroRNAS (miRNAS: a class of short non-coding RNAs) are emerging as important agents of post transcriptional gene regulation and integral components of gene networks. MiRNAs have been strongly linked to stem cells, which have a remarkable dual role in development. They can either continuously replenish themselves (self-renewal), or differentiate into cells that execute a limited number of specific actions (pluripotence).In order to identify novel miRNAs from narrow windows of development we carried out an in silico search for micro-conserved elements (MCE) in adult tissue progenitor transcript sequences. A plethora of previously unknown miRNA candidates were revealed including 545 small RNAs that are enriched in embryonic stem (ES) cells over adult cells. Approximately 20% of these novel candidates are down-regulated in ES (Dicer(-/-)) ES cells that are impaired in miRNA maturation. The ES-enriched miRNA candidates exhibit distinct and opposite expression trends from mmu-mirs (an abundant class in adult tissues) during retinoic acid (RA)-induced ES cell differentiation. Significant perturbation of trends is found in both miRNAs and novel candidates in ES (GCNF(-/-)) cells, which display loss of repression of pluripotence genes upon differentiation.Combining expression profile information with miRNA target prediction, we identified miRNA-mRNA pairs that correlate with ES cell pluripotence and differentiation. Perturbation of these pairs in the ES (GCNF(-/-)) mutant suggests a role for miRNAs in the core regulatory networks underlying ES cell self-renewal, pluripotence and differentiation.

Age-related defects in stem cells can limit proper tissue maintenance and hence contribute to a shortened lifespan. Using highly purified hematopoietic stem cells from mice aged 2 to 21 mo, we demonstrate a deficit in function yet an increase in stem cell number with advancing age. Expression analysis of more than 14,000 genes identified 1,500 that were age-induced and 1,600 that were age-repressed. Genes associated with the stress response, inflammation, and protein aggregation dominated the up-regulated expression profile, while the down-regulated profile was marked by genes involved in the preservation of genomic integrity and chromatin remodeling. Many chromosomal regions showed coordinate loss of transcriptional regulation; an overall increase in transcriptional activity with age and inappropriate expression of genes normally regulated by epigenetic mechanisms was also observed. Hematopoietic stem cells from early-aging mice expressing a mutant p53 allele reveal that aging of stem cells can be uncoupled from aging at an organismal level. These studies show that hematopoietic stem cells are not protected from aging. Instead, loss of epigenetic regulation at the chromatin level may drive both functional attenuation of cells, as well as other manifestations of aging, including the increased propensity for neoplastic transformation.

BACKGROUND: Array Comparative Genomic Hybridization (a-CGH) is a powerful molecular cytogenetic tool to detect genomic imbalances and study disease mechanism and pathogenesis. We report our experience with the clinical implementation of this high resolution human genome analysis, referred to as Chromosomal Microarray Analysis (CMA). METHODS AND FINDINGS: CMA was performed clinically on 2513 postnatal samples from patients referred with a variety of clinical phenotypes. The initial 775 samples were studied using CMA array version 4 and the remaining 1738 samples were analyzed with CMA version 5 containing expanded genomic coverage. Overall, CMA identified clinically relevant genomic imbalances in 8.5% of patients: 7.6% using V4 and 8.9% using V5. Among 117 cases referred for additional investigation of a known cytogenetically detectable rearrangement, CMA identified the majority (92.5%) of the genomic imbalances. Importantly, abnormal CMA findings were observed in 5.2% of patients (98/1872) with normal karyotypes/FISH results, and V5, with expanded genomic coverage, enabled a higher detection rate in this category than V4. For cases without cytogenetic results available, 8.0% (42/524) abnormal CMA results were detected; again, V5 demonstrated an increased ability to detect abnormality. Improved diagnostic potential of CMA is illustrated by 90 cases identified with 51 cryptic microdeletions and 39 predicted apparent reciprocal microduplications in 13 specific chromosomal regions associated with 11 known genomic disorders. In addition, CMA identified copy number variations (CNVs) of uncertain significance in 262 probands; however, parental studies usually facilitated clinical interpretation. Of these, 217 were interpreted as familial variants and 11 were determined to be de novo; the remaining 34 await parental studies to resolve the clinical significance. CONCLUSIONS: This large set of clinical results demonstrates the significantly improved sensitivity of CMA for the detection of clinically relevant genomic imbalances and highlights the need for comprehensive genetic counseling to facilitate accurate clinical correlation and interpretation.

Hematopoietic stem cells replenish all the cells of the blood throughout the lifetime of an animal. Although thousands of stem cells reside in the bone marrow, only a few contribute to blood production at any given time. Nothing is known about the differences between individual stem cells that dictate their particular state of activation readiness. To examine such differences between individual stem cells, we determined the global gene expression profile of 12 single stem cells using microarrays. We showed that at least half of the genetic expression variability between 12 single cells profiled was due to biological variation in 44% of the genes analyzed. We also identified specific genes with high biological variance that are candidates for influencing the state of readiness of individual hematopoietic stem cells, and confirmed the variability of a subset of these genes using single-cell real-time PCR. Because apparent variation of some genes is likely due to technical factors, we estimated the degree of biological versus technical variation for each gene using identical RNA samples containing an RNA amount equivalent to that of single cells. This enabled us to identify a large cohort of genes with low technical variability whose expression can be reliably measured on the arrays at the single-cell level. These data have established that gene expression of individual stem cells varies widely, despite extremely high phenotypic homogeneity. Some of this variation is in key regulators of stem cell activity, which could account for the differential responses of particular stem cells to exogenous stimuli. The capacity to accurately interrogate individual cells for global gene expression will facilitate a systems approach to biological processes at a single-cell level.

Stem cells resident in adult tissues are principally quiescent, yet harbor enormous capacity for proliferation to achieve self renewal and to replenish their tissue constituents. Although a single hematopoietic stem cell (HSC) can generate sufficient primitive progeny to repopulate many recipients, little is known about the molecular mechanisms that maintain their potency or regulate their self renewal. Here we have examined the gene expression changes that occur over a time course when HSCs are induced to proliferate and return to quiescence in vivo. These data were compared to data representing differences between naturally proliferating fetal HSCs and their quiescent adult counterparts. Bioinformatic strategies were used to group time-ordered gene expression profiles generated from microarrays into signatures of quiescent and dividing stem cells. A novel method for calculating statistically significant enrichments in Gene Ontology groupings for our gene lists revealed elemental subgroups within the signatures that underlie HSC behavior, and allowed us to build a molecular model of the HSC activation cycle. Initially, quiescent HSCs evince a state of readiness. The proliferative signal induces a preparative state, which is followed by active proliferation divisible into early and late phases. Re-induction of quiescence involves changes in migratory molecule expression, prior to reestablishment of homeostasis. We also identified two genes that increase in both gene and protein expression during activation, and potentially represent new markers for proliferating stem cells. These data will be of use in attempts to recapitulate the HSC self renewal process for therapeutic expansion of stem cells, and our model may correlate with acquisition of self renewal characteristics by cancer stem cells.

Purpose: The variome of the Turkish (TK) population, a population with a considerable history of admixture and consanguinity, has not been deeply investigated for insights on the genomic architecture of disease. Methods: We generated and analyzed a database of variants derived from exome sequencing data of 773 TK unrelated, clinically affected individuals with various suspected Mendelian disease traits and 643 unaffected relatives. Results: Using uniform manifold approximation and projection, we showed that the TK genomes are more similar to those of Europeans and consist of 2 main subpopulations: clusters 1 and 2 (N = 235 and 1181, respectively), which differ in admixture proportion and variome (https://turkishvariomedb.shinyapps.io/tvdb/). Furthermore, the higher inbreeding coefficient values observed in the TK affected compared with unaffected individuals correlated with a larger median span of long-sized (>2.64 Mb) runs of homozygosity (ROH) regions (P value = 2.09e-18). We show that long-sized ROHs are more likely to be formed on recently configured haplotypes enriched for rare homozygous deleterious variants in the TK affected compared with TK unaffected individuals (P value = 3.35e-11). Analysis of genotype-phenotype correlations reveals that genes with rare homozygous deleterious variants in long-sized ROHs provide the most comprehensive set of molecular diagnoses for the observed disease traits with a systematic quantitative analysis of Human Phenotype Ontology terms. Conclusion: Our findings support the notion that novel rare variants on newly configured haplotypes arising within the recent past generations of a family or clan contribute significantly to recessive disease traits in the TK population.