scholarly journals Individualized VDJ recombination predisposes the available Ig sequence space

2021 ◽  
Author(s):  
Andrei Slabodkin ◽  
Maria Chernigovskaya ◽  
Ivana Mikocziova ◽  
Rahmad Akbar ◽  
Lonneke Scheffer ◽  
...  
Keyword(s):  
Sequence Space ◽  
Distance Measure ◽  
Allelic Variation ◽  
Inbred Mice ◽  
Individualized Medicine ◽  
Monozygotic Twins ◽  
Antigen Recognition ◽  
Sequencing Data ◽  
Vdj Recombination ◽  
Individual Comparison

The process of recombination between variable (V), diversity (D), and joining (J) immunoglobulin (Ig) gene segments determines an individual's naive Ig repertoire and, consequently, (auto)antigen recognition. VDJ recombination follows probabilistic rules that can be modeled statistically. So far, it remains unknown whether VDJ recombination rules differ between individuals. If these rules differed, identical (auto)antigen-specific Ig sequences would be generated with individual-specific probabilities, signifying that the available Ig sequence space is individual specific. We devised a sensitivity-tested distance measure that enables inter-individual comparison of VDJ recombination models. We discovered, accounting for several sources of noise as well as allelic variation in Ig sequencing data, that not only unrelated individuals but also human monozygotic twins and even inbred mice possess statistically distinguishable immunoglobulin recombination models. This suggests that, in addition to genetic, there is also nongenetic modulation of VDJ recombination. We demonstrate that population-wide individualized VDJ recombination can result in orders of magnitude of difference in the probability to generate (auto)antigen-specific Ig sequences. Our findings have implications for immune receptor–based individualized medicine approaches relevant to vaccination, infection, and autoimmunity.

scholarly journals Individualized VDJ recombination predisposes the available Ig sequence space

2021 ◽  
Author(s):  
Andrei Slabodkin ◽  
Maria Chernigovskaya ◽  
Ivana Mikocziova ◽  
Rahmad Akbar ◽  
Lonneke Scheffer ◽  
...  
Keyword(s):  
Sequence Space ◽  
Distance Measure ◽  
Allelic Variation ◽  
Inbred Mice ◽  
Individualized Medicine ◽  
Monozygotic Twins ◽  
Antigen Recognition ◽  
Sequencing Data ◽  
Vdj Recombination ◽  
Individual Comparison

The process of recombination between variable (V), diversity (D), and joining (J) immunoglobulin (Ig) gene segments determines an individual's naive Ig repertoire, and consequently (auto)antigen recognition. VDJ recombination follows probabilistic rules that can be modeled statistically. So far, it remains unknown whether VDJ recombination rules differ between individuals. If these rules differed, identical (auto)antigen-specific Ig sequences would be generated with individual-specific probabilities, signifying that the available Ig sequence space is individual-specific. We devised a sensitivity-tested distance measure that enables inter-individual comparison of VDJ recombination models. We discovered, accounting for several sources of noise as well as allelic variation in Ig sequencing data, that not only unrelated individuals but also human monozygotic twins and even inbred mice possess statistically distinguishable immunoglobulin recombination models. This suggests that, in addition to genetic, there is also non-genetic modulation of VDJ recombination. We demonstrate that population-wide individualized VDJ recombination can result in orders of magnitude of difference in the probability to generate (auto)antigen-specific Ig sequences. Our findings have implications for immune receptor-based individualized medicine approaches relevant to vaccination, infection, and autoimmunity.

scholarly journals SOS: online probability estimation and generation of T-and B-cell receptors

2020 ◽  
Vol 36 (16) ◽  
pp. 4510-4512
Author(s):  
Giulio Isacchini ◽  
Carlos Olivares ◽  
Armita Nourmohammad ◽  
Aleksandra M Walczak ◽  
Thierry Mora
Keyword(s):  
B Cell ◽  
High Throughput Sequencing ◽  
B Cell Receptors ◽  
Sequencing Data ◽  
Vdj Recombination ◽  
Web Based ◽  
Cell Receptors ◽  
High Throughput Sequencing Data ◽  
Selection Probabilities ◽  
Selection Of

Abstract Summary Recent advances in modelling VDJ recombination and subsequent selection of T- and B-cell receptors provide useful tools to analyse and compare immune repertoires across time, individuals and tissues. A suite of tools—IGoR, OLGA and SONIA—have been publicly released to the community that allow for the inference of generative and selection models from high-throughput sequencing data. However, using these tools requires some scripting or command-line skills and familiarity with complex datasets. As a result, the application of the above models has not been available to a broad audience. In this application note, we fill this gap by presenting Simple OLGA & SONIA (SOS), a web-based interface where users with no coding skills can compute the generation and post-selection probabilities of their sequences, as well as generate batches of synthetic sequences. The application also functions on mobile phones. Availability and implementation SOS is freely available to use at sites.google.com/view/statbiophysens/sos with source code at github.com/statbiophys/sos.

scholarly journals MONOZYGOTIC VS. DIZYGOTIC TWIN BEHAVIOR IN ARTIFICIAL MOUSE TWINS

Genetics ◽  
1984 ◽  
Vol 106 (3) ◽  
pp. 463-477
Author(s):  
E Baunack ◽  
U Falk ◽  
K Gärtner
Keyword(s):  
Rank Order ◽  
Inbred Mice ◽  
Monozygotic Twins ◽  
Behavioral Characteristics ◽  
Behavioral Differences ◽  
Dizygotic Twins ◽  
Copulatory Pattern ◽  
Early Ontogenetic Stage ◽  
Intromission Latency ◽  
High Degree

ABSTRACT Adult inbred mice of an isogenic strain (AKR/NHan or C57BL/6J Han) differ in social (sexual and agonistic), emotional and psychomotoric behavior, depending on the kind of manipulation to which they were subjected at an early ontogenetic stage. Monozygotic twins (MZT) from eight-cell stages halved and transferred to uterine foster mothers were compared with dizygotic twins (DZT) from nonreduced but transferred eight-cell stages and with naturally born animals (NBA). Generally, early embryonic conditions predict the behavioral characteristics of the adult animals to a high degree. The MZT are motorially less active, less emotional, less aggressive and less socially interested than DZT and NBA. In tests of spontaneous social behavior (allogrooming, anogenital licking, mounting, fighting), as well as in tests for emotionality (open field: crossed fields and defecation), these behavioral patterns occurred less frequently in MZT than in DZT; the NBA were mostly intermediate. The copulatory pattern of male MZT differs from that of male DZT by a shortage of intromission latency and duration; furthermore, MZT pairs do not build up a steady rank order in competitive copulation tests, as opposed to DZT and NBA pairs. In a test for psychomotoric behavior (swimming), the MZT prefer "floating" as a survival strategy, wheras the DZT and NBA prefer "adult swimming." Therefore, it can be concluded that these behavioral differences may be caused by the particular psychosocial environment in which the twins grow up or may be due to early prenatal peculiarities, such as inadequate synchronization of the developmental status of uterus and embryo.

scholarly journals DR2S: An Integrated Algorithm Providing Reference-Grade Haplotype Sequences from Heterozygous Samples

2020 ◽  
Author(s):  
Steffen Klasberg ◽  
Alexander H. Schmidt ◽  
Vinzenz Lange ◽  
Gerhard Schöfl
Keyword(s):  
Allelic Variation ◽  
R Package ◽  
Full Length ◽  
Reference Sequence ◽  
Read Length ◽  
Sequencing Data ◽  
High Quality ◽  
Reference Allele ◽  
Sequencing Technologies ◽  
Generation Sequencing

AbstractBackgroundHigh resolution HLA genotyping of donors and recipients is a crucially important prerequisite for haematopoetic stem-cell transplantation and relies heavily on the quality and completeness of immuno-genetic reference sequence databases of allelic variation.ResultsHere, we report on DR2S, an R package that leverages the strengths of two sequencing technologies – the accuracy of next-generation sequencing with the read length of third-generation sequencing technologies like PacBio’s SMRT sequencing or ONT’s nanopore sequencing – to reconstruct fully-phased high-quality full-length haplotype sequences. Although optimised for HLA and KIR genes, DR2S is applicable to all loci with known reference sequences provided that full-length sequencing data is available for analysis. In addition, DR2S integrates supporting tools for easy visualisation and quality control of the reconstructed haplotype to ensure suitability for submission to public allele databases.ConclusionsDR2S is a largely automated workflow designed to create high-quality fully-phased reference allele sequences for highly polymorphic gene regions such as HLA or KIR. It has been used by biologists to successfully characterise and submit more than 500 HLA alleles and more than 500 KIR alleles to the IPD-IMGT/HLA and IPD-KIR databases.

scholarly journals Characterization and Mapping of retr04, retr05 and retr06 Broad-Spectrum Resistances to Turnip Mosaic Virus in Brassica juncea, and the Development of Robust Methods for Utilizing Recalcitrant Genotyping Data

2022 ◽  
Vol 12 ◽  
Author(s):  
Lawrence E. Bramham ◽  
Tongtong Wang ◽  
Erin E. Higgins ◽  
Isobel A. P. Parkin ◽  
Guy C. Barker ◽  
...  
Keyword(s):  
Mosaic Virus ◽  
Brassica Juncea ◽  
Allelic Variation ◽  
Snp Array ◽  
Genotyping By Sequencing ◽  
Turnip Mosaic Virus ◽  
Interactive Effects ◽  
Sequencing Data ◽  
Array Data ◽  
Tumv Resistance

Turnip mosaic virus (TuMV) induces disease in susceptible hosts, notably impacting cultivation of important crop species of the Brassica genus. Few effective plant viral disease management strategies exist with the majority of current approaches aiming to mitigate the virus indirectly through control of aphid vector species. Multiple sources of genetic resistance to TuMV have been identified previously, although the majority are strain-specific and have not been exploited commercially. Here, two Brassica juncea lines (TWBJ14 and TWBJ20) with resistance against important TuMV isolates (UK 1, vVIR24, CDN 1, and GBR 6) representing the most prevalent pathotypes of TuMV (1, 3, 4, and 4, respectively) and known to overcome other sources of resistance, have been identified and characterized. Genetic inheritance of both resistances was determined to be based on a recessive two-gene model. Using both single nucleotide polymorphism (SNP) array and genotyping by sequencing (GBS) methods, quantitative trait loci (QTL) analyses were performed using first backcross (BC1) genetic mapping populations segregating for TuMV resistance. Pairs of statistically significant TuMV resistance-associated QTLs with additive interactive effects were identified on chromosomes A03 and A06 for both TWBJ14 and TWBJ20 material. Complementation testing between these B. juncea lines indicated that one resistance-linked locus was shared. Following established resistance gene nomenclature for recessive TuMV resistance genes, these new resistance-associated loci have been termed retr04 (chromosome A06, TWBJ14, and TWBJ20), retr05 (A03, TWBJ14), and retr06 (A03, TWBJ20). Genotyping by sequencing data investigated in parallel to robust SNP array data was highly suboptimal, with informative data not established for key BC1 parental samples. This necessitated careful consideration and the development of new methods for processing compromised data. Using reductive screening of potential markers according to allelic variation and the recombination observed across BC1 samples genotyped, compromised GBS data was rendered functional with near-equivalent QTL outputs to the SNP array data. The reductive screening strategy employed here offers an alternative to methods relying upon imputation or artificial correction of genotypic data and may prove effective for similar biparental QTL mapping studies.

scholarly journals An NGS Workflow Blueprint for DNA Sequencing Data and Its Application in Individualized Molecular Oncology

2015 ◽  
Vol 14s5 ◽  
pp. CIN.S30793 ◽  
Author(s):  
Jian Li ◽  
Aarif Mohamed Nazeer Batcha ◽  
Björn Gaining ◽  
Ulrich R. Mansmann
Keyword(s):  
Data Storage ◽  
Individualized Medicine ◽  
Integrated Analysis ◽  
Sequencing Data ◽  
Molecular Oncology ◽  
Analysis Workflow ◽  
Sequencing Quality ◽  
Technical Simplicity ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data

Next-generation sequencing (NGS) technologies that have advanced rapidly in the past few years possess the potential to classify diseases, decipher the molecular code of related cell processes, identify targets for decision-making on targeted therapy or prevention strategies, and predict clinical treatment response. Thus, NGS is on its way to revolutionize oncology. With the help of NGS, we can draw a finer map for the genetic basis of diseases and can improve our understanding of diagnostic and prognostic applications and therapeutic methods. Despite these advantages and its potential, NGS is facing several critical challenges, including reduction of sequencing cost, enhancement of sequencing quality, improvement of technical simplicity and reliability, and development of semiautomated and integrated analysis workflow. In order to address these challenges, we conducted a literature research and summarized a four-stage NGS workflow for providing a systematic review on NGS-based analysis, explaining the strength and weakness of diverse NGS-based software tools, and elucidating its potential connection to individualized medicine. By presenting this four-stage NGS workflow, we try to provide a minimal structural layout required for NGS data storage and reproducibility.

HIF-1 regulates heritable variation and allele expression phenotypes of the macrophage immune response gene SLC11A1 from a Z-DNA–forming microsatellite

Blood ◽  
2007 ◽  
Vol 110 (8) ◽  
pp. 3039-3048 ◽  
Author(s):  
Henry K. Bayele ◽  
Carole Peyssonnaux ◽  
Alexandra Giatromanolaki ◽  
Wagner W. Arrais-Silva ◽  
Hiba S. Mohamed ◽  
...  
Keyword(s):  
Disease Risk ◽  
Allelic Variation ◽  
Inflammatory Diseases ◽  
Inbred Mice ◽  
Hypoxia Inducible Factor ◽  
Immune Response Gene ◽  
Allelic Association ◽  
Heritable Variation ◽  
Allele Expression ◽  
Z Dna

AbstractThe Ity/Lsh/Bcg locus encodes the macrophage protein Slc11a1/Nramp1, which protects inbred mice against infection by diverse intracellular pathogens including Leishmania, Mycobacterium, and Salmonella. Human susceptibility to infectious and inflammatory diseases, including rheumatoid arthritis, inflammatory bowel disease, and tuberculosis, shows allelic association with a highly polymorphic regulatory, Z-DNA–forming microsatellite of (GT/AC)n dinucleotides within the proximal SLC11A1 promoter. We surmised that cis-acting allelic polymorphisms may underlie heritable differences in SLC11A1 expression and phenotypic variation in disease risk. However, it is unclear what may underlie such variation in SLC11A1 allele expression. Here we show that hypoxia-inducible Factor 1 (HIF-1) regulates allelic variation in SLC11A1 expression by binding directly to the microsatellite during macrophage activation by infection or inflammation. Targeted Hif-1α ablation in murine macrophages attenuated Slc11a11 expression and responsiveness to S typhimurium infection. Our data also showed that HIF-1 may be functionally linked to complex prototypical inflammatory diseases associated with certain SLC11A1 alleles. As these alleles are highly polymorphic, our finding suggests that HIF-1 may influence heritable variation in SLC11A1-dependent innate resistance to infection and inflammation within and between populations. This report also suggests that microsatellites may play critical roles in the directional evolution of complex heritable traits by regulating gene expression phenotypes.

scholarly journals Equivalent DNA methylation variation between monozygotic co-twins and unrelated individuals reveals universal epigenetic inter-individual dissimilarity

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Benjamin Planterose Jiménez ◽  
Fan Liu ◽  
Amke Caliebe ◽  
Diego Montiel González ◽  
Jordana T. Bell ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Adipose Tissue ◽  
Measurement Error ◽  
Monozygotic Twins ◽  
Monozygotic Twin ◽  
Equivalence Testing ◽  
Sequencing Data ◽  
Stochastic Variation ◽  
Developing Neurons ◽  
Methylation Variation

Abstract Background Although the genomes of monozygotic twins are practically identical, their methylomes may evolve divergently throughout their lifetime as a consequence of factors such as the environment or aging. Particularly for young and healthy monozygotic twins, DNA methylation divergence, if any, may be restricted to stochastic processes occurring post-twinning during embryonic development and early life. However, to what extent such stochastic mechanisms can systematically provide a stable source of inter-individual epigenetic variation remains uncertain until now. Results We enriched for inter-individual stochastic variation by using an equivalence testing-based statistical approach on whole blood methylation microarray data from healthy adolescent monozygotic twins. As a result, we identified 333 CpGs displaying similarly large methylation variation between monozygotic co-twins and unrelated individuals. Although their methylation variation surpasses measurement error and is stable in a short timescale, susceptibility to aging is apparent in the long term. Additionally, 46% of these CpGs were replicated in adipose tissue. The identified sites are significantly enriched at the clustered protocadherin loci, known for stochastic methylation in developing neurons. We also confirmed an enrichment in monozygotic twin DNA methylation discordance at these loci in whole genome bisulfite sequencing data from blood and adipose tissue. Conclusions We have isolated a component of stochastic methylation variation, distinct from genetic influence, measurement error, and epigenetic drift. Biomarkers enriched in this component may serve in the future as the basis for universal epigenetic fingerprinting, relevant for instance in the discrimination of monozygotic twin individuals in forensic applications, currently impossible with standard DNA profiling.

scholarly journals Clustering on Human Microbiome Sequencing Data: A Distance-Based Unsupervised Learning Model

2020 ◽  
Vol 8 (10) ◽  
pp. 1612
Author(s):  
Dongyang Yang ◽  
Wei Xu
Keyword(s):  
Beta Diversity ◽  
Clustering Algorithm ◽  
Distance Measure ◽  
Human Microbiome ◽  
Operational Taxonomic Unit ◽  
Distance Measures ◽  
Clustering Methods ◽  
Sequencing Data ◽  
Diversity Measure ◽  
Parkinson’S Diseases

Modeling and analyzing human microbiome allows the assessment of the microbial community and its impacts on human health. Microbiome composition can be quantified using 16S rRNA technology into sequencing data, which are usually skewed and heavy-tailed with excess zeros. Clustering methods are useful in personalized medicine by identifying subgroups for patients stratification. However, there is currently a lack of standardized clustering method for the complex microbiome sequencing data. We propose a clustering algorithm with a specific beta diversity measure that can address the presence-absence bias encountered for sparse count data and effectively measure the sample distances for sample stratification. Our distance measure used for clustering is derived from a parametric based mixture model producing sample-specific distributions conditional on the observed operational taxonomic unit (OTU) counts and estimated mixture weights. The method can provide accurate estimates of the true zero proportions and thus construct a precise beta diversity measure. Extensive simulation studies have been conducted and suggest that the proposed method achieves substantial clustering improvement compared with some widely used distance measures when a large proportion of zeros is presented. The proposed algorithm was implemented to a human gut microbiome study on Parkinson’s diseases to identify distinct microbiome states with biological interpretations.

Sign in / Sign up

Export Citation Format

Share Document