scholarly journals Genome-wide recombination map construction from single individuals using linked-read sequencing

2018 ◽  
Author(s):  
Andreea Dréau ◽  
Vrinda Venu ◽  
Ludmila Gaspar ◽  
Felicity C. Jones
Keyword(s):  
Low Cost ◽  
Genomic Diversity ◽  
Single Individual ◽  
Recombination Rates ◽  
Recombination Hotspots ◽  
Map Construction ◽  
Genome Wide ◽  
Genomic Location ◽  
Sperm Dna ◽  
Opening Up

Meiotic recombination is a major molecular mechanism generating genomic diversity. Recombination rates vary across the genome, often involving localized crossover “hotspots” and “coldspots”. Studying the molecular basis and mechanism underlying this variation within and among individuals has been challenging due to the high cost and effort required to construct individualized genome-wide maps of recombination crossovers. In this study we introduce a new method to detect recombination crossovers across the genome from sperm DNA using Illumina sequencing of linked-read libraries produced using 10X Genomics technology. We leverage the long range information provided by the linked short reads to phase and assign haplotype states to each DNA molecule. When applied to DNA from gametes of a diploid organism, the majority of linked-read molecules can be used to faithfully reconstruct an individual’s two haplotypes present at each location in the genome. A valuable rare fraction of molecules that span meiotic crossovers between the two chromosome haplotypes can then be isolated from the broader population of nonrecombinant molecules. Our pipeline, called ReMIX, allows us to characterize the genomic location and intensity of meiotic crossovers in a single individual and faithfully detects previously described recombination hotspots discovered by studies using mapping panels in mice. With a median crossover resolution of the mouse and stickleback being 15kb and 23kb respectively, ReMIX provides a powerful, high-throughput, low-cost approach to quantify recombination variation across the genome opening up numerous opportunities to study recombination variation with high genomic resolution in multiple individuals. ReMIX source code is available at at https://github.com/adreau/ReMIX.

scholarly journals Genome-wide recombination map construction from single individuals using linked-read sequencing

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Andreea Dréau ◽  
Vrinda Venu ◽  
Elena Avdievich ◽  
Ludmila Gaspar ◽  
Felicity C. Jones
Keyword(s):  
Meiotic Recombination ◽  
Molecular Basis ◽  
Low Cost ◽  
Single Individual ◽  
Recombination Rates ◽  
Recombination Hotspots ◽  
Map Construction ◽  
Genome Wide ◽  
Genomic Location ◽  
Exciting Opportunity

Abstract Meiotic recombination rates vary across the genome, often involving localized crossover hotspots and coldspots. Studying the molecular basis and mechanisms underlying this variation has been challenging due to the high cost and effort required to construct individualized genome-wide maps of recombination crossovers. Here we introduce a new method, called ReMIX, to detect crossovers from gamete DNA of a single individual using Illumina sequencing of 10X Genomics linked-read libraries. ReMIX reconstructs haplotypes and identifies the valuable rare molecules spanning crossover breakpoints, allowing quantification of the genomic location and intensity of meiotic recombination. Using a single mouse and stickleback fish, we demonstrate how ReMIX faithfully recovers recombination hotspots and landscapes that have previously been built using hundreds of offspring. ReMIX provides a high-resolution, high-throughput, and low-cost approach to quantify recombination variation across the genome, providing an exciting opportunity to study recombination among multiple individuals in diverse organisms.

scholarly journals A Coalescent Model of Recombination Hotspots

Genetics ◽  
2003 ◽  
Vol 164 (1) ◽  
pp. 407-417 ◽  
Author(s):  
Carsten Wiuf ◽  
David Posada
Keyword(s):  
Current Debate ◽  
Expected Number ◽  
Recombination Rates ◽  
Coalescent Model ◽  
Recombination Hotspots ◽  
Snp Data ◽  
Genome Wide ◽  
Experimental Findings ◽  
Historical Recombination ◽  
Block Structured

Abstract Recent experimental findings suggest that the assumption of a homogeneous recombination rate along the human genome is too naive. These findings point to block-structured recombination rates; certain regions (called hotspots) are more prone than other regions to recombination. In this report a coalescent model incorporating hotspot or block-structured recombination is developed and investigated analytically as well as by simulation. Our main results can be summarized as follows: (1) The expected number of recombination events is much lower in a model with pure hotspot recombination than in a model with pure homogeneous recombination, (2) hotspots give rise to large variation in recombination rates along the genome as well as in the number of historical recombination events, and (3) the size of a (nonrecombining) block in the hotspot model is likely to be overestimated grossly when estimated from SNP data. The results are discussed with reference to the current debate about block-structured recombination and, in addition, the results are compared to genome-wide variation in recombination rates. A number of new analytical results about the model are derived.

scholarly journals Recombining without hotspots: A comprehensive evolutionary portrait of recombination in two closely related species of Drosophila

2015 ◽  
Author(s):  
Caiti Smukowski Heil ◽  
Chris Ellison ◽  
Matthew Dubin ◽  
Mohamed Noor
Keyword(s):  
Recombination Rate ◽  
Multiple Scales ◽  
Sequence Data ◽  
Scale Effects ◽  
Recombination Rates ◽  
Recombination Hotspots ◽  
Genome Wide ◽  
Genomic Landscape ◽  
Species Specific

Meiotic recombination rate varies across the genome within and between individuals, populations, and species in virtually all taxa studied. In almost every species, this variation takes the form of discrete recombination hotspots, determined in Metazoans by a protein called PRDM9. Hotspots and their determinants have a profound effect on the genomic landscape, and share certain features that extend across the tree of life. Drosophila, in contrast, are anomalous in their absence of hotspots, PRDM9, and other species-specific differences in the determination of recombination. To better understand the evolution of meiosis and general patterns of recombination across diverse taxa, we present what may be the most comprehensive portrait of recombination to date, combining contemporary recombination estimates from each of two sister species along with historic estimates of recombination using linkage-disequilibrium-based approaches derived from sequence data from both species. Using Drosophila pseudoobscura and Drosophila miranda as a model system, we compare recombination rate between species at multiple scales, and we replicate the pattern seen in human-chimpanzee that recombination rate is conserved at broad scales and more divergent at finer scales. We also find evidence of a species-wide recombination modifier, resulting in both a present and historic genome wide elevation of recombination rates in D. miranda, and identify broad scale effects on recombination from the presence of an inter-species inversion. Finally, we reveal an unprecedented view of the distribution of recombination in D. pseudoobscura, illustrating patterns of linked selection and where recombination is taking place. Overall, by combining these estimation approaches, we highlight key similarities and differences in recombination between Drosophila and other organisms.

scholarly journals Chromosomal assembly and analyses of genome-wide recombination rates in the forest pathogenic fungus Armillaria ostoyae

2019 ◽  
Author(s):  
Renate Heinzelmann ◽  
Daniel Rigling ◽  
György Sipos ◽  
Martin Münsterkötter ◽  
Daniel Croll
Keyword(s):  
Pathogenic Fungus ◽  
Snp Markers ◽  
Rate Variation ◽  
Recombination Rates ◽  
Evolutionary Trajectory ◽  
Armillaria Ostoyae ◽  
Recombination Hotspots ◽  
Genome Wide ◽  
A Genome ◽  
Taxonomic Groups

AbstractRecombination shapes the evolutionary trajectory of populations and plays an important role in the faithful transmission of chromosomes during meiosis. Levels of sexual reproduction and recombination are important properties of host-pathogen interactions because the speed of antagonistic co-evolution depends on the ability of hosts and pathogens to generate genetic variation. However, our understanding of the importance of recombination is limited because large taxonomic groups remain poorly investigated. Here, we analyze recombination rate variation in the basidiomycete fungus Armillaria ostoyae, which is an aggressive pathogen on a broad range of conifers and other trees. We constructed a dense genetic map using 198 single basidiospore progeny from a cross. Progeny were genotyped at a genome-wide set of single nucleotide polymorphism (SNP) markers using double digest restriction site associated DNA sequencing (ddRADseq). Based on a linkage map of on 11,700 SNPs spanning 1007.5 cM, we assembled genomic scaffolds into 11 putative chromosomes of a total genome size of 56.6 Mb. We identified 1984 crossover events among all progeny and found that recombination rates were highly variable along chromosomes. Recombination hotspots tended to be in regions close to the telomeres and were more gene-poor than the genomic background. Genes in proximity to recombination hotspots were encoding on average shorter proteins and were enriched for pectin degrading enzymes. Our analyses enable more powerful population and genome-scale studies of a major tree pathogen.

Opening up a New Field of Modern Medical Research 1

2020 ◽  
Author(s):  
Xiaoguang Li
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Human Body ◽  
Low Cost ◽  
Acupuncture Point ◽  
Modern Medicine ◽  
Body Structure ◽  
Special Effect ◽  
Special Knowledge ◽  
Opening Up

Modern medicine tells us that the human body is an organism composed of heart, lung, liver, kidney, spleen, stomach, brain, nerves, muscles, bones, blood vessels, blood and so on, while traditional Chinese medicine believes that besides these tissues and organs, the human body still has another part of the structure, traditional Chinese medicine calls them Jing Luo and Shu Xue. Jing Luo means the longitudinal line of the human body and the accompanying net, translated into English Meridians and Collaterals. Shu Xue means holes distributed on Jing Luo and outside Jing Luo, because stimulating Shu Xue's position by acupuncture, massage and other methods can cure diseases, so Shu Xue is translated into English acupuncture point, abbreviated as acupoint or point. Meridians and acupoints are the special knowledge of human body structure in traditional Chinese medicine. Traditional Chinese medicine not only draws the distribution map of the meridians and acupoints in the human body, but also has been using them to treat diseases for thousands of years. There are hundreds of these acupoints, stimulating each one by acupuncture, massage or other methods will have a special effect on the human body and can treat various diseases. But what effect does stimulating every acupoint have on the human body so that it can treat various diseases? The discussion of traditional Chinese medicine is vague and incomprehensible, and can not be proved by experiments. According to the author's research for more than 30 years, this paper makes a clear and accurate exposition of the effects on the human body and diseases that can be treated with acupoint massage. These statements can be proved by experiments, so they are believed to be reliable. It is hoped that meridians, acupoints and massage therapy can be incorporated into modern medicine and become a part of modern medicine after being proved by others through experiments. Massaging acupoints can not only treat many diseases that are difficult to be treated with drugs, but also have simple methods and low cost.

Artificial Intelligence for epigenetics: towards personalized medicine

2020 ◽  
Vol 27 ◽  
Author(s):  
Giulia De Riso ◽  
Sergio Cocozza
Keyword(s):  
Biological Sciences ◽  
Artificial Intelligence ◽  
Personalized Medicine ◽  
Molecular Mechanisms ◽  
Genomic Sequence ◽  
Health Care Interventions ◽  
Genome Wide ◽  
Genetic And Environmental Factors ◽  
Opening Up ◽  
Omic Data

: Epigenetics is a field of biological sciences focused on the study of reversible, heritable changes in gene function not due to modifications of the genomic sequence. These changes are the result of a complex cross-talk between several molecular mechanisms, that is in turn orchestrated by genetic and environmental factors. The epigenetic profile captures the unique regulatory landscape and the exposure to environmental stimuli of an individual. It thus constitutes a valuable reservoir of information for personalized medicine, which is aimed at customizing health-care interventions based on the unique characteristics of each individual. Nowadays, the complex milieu of epigenomic marks can be studied at the genome-wide level thanks to massive, highthroughput technologies. This new experimental approach is opening up new and interesting knowledge perspectives. However, the analysis of these complex omic data requires to face important analytic issues. Artificial Intelligence, and in particular Machine Learning, are emerging as powerful resources to decipher epigenomic data. In this review, we will first describe the most used ML approaches in epigenomics. We then will recapitulate some of the recent applications of ML to epigenomic analysis. Finally, we will provide some examples of how the ML approach to epigenetic data can be useful for personalized medicine.

scholarly journals Development and validation of genome-wide InDel markers with high levels of polymorphism in bitter gourd (Momordica charantia)

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Junjie Cui ◽  
Jiazhu Peng ◽  
Jiaowen Cheng ◽  
Kailin Hu
Keyword(s):  
Genetic Map ◽  
Average Density ◽  
Momordica Charantia ◽  
Bitter Gourd ◽  
Map Construction ◽  
Indel Markers ◽  
Genome Wide ◽  
Indel Polymorphisms ◽  
Molecular Marker Development ◽  
Development And Validation

Abstract Background The preferred choice for molecular marker development is identifying existing variation in populations through DNA sequencing. With the genome resources currently available for bitter gourd (Momordica charantia), it is now possible to detect genome-wide insertion-deletion (InDel) polymorphisms among bitter gourd populations, which guides the efficient development of InDel markers. Results Here, using bioinformatics technology, we detected 389,487 InDels from 61 Chinese bitter gourd accessions with an average density of approximately 1298 InDels/Mb. Then we developed a total of 2502 unique InDel primer pairs with a polymorphism information content (PIC) ≥0.6 distributed across the whole genome. Amplification of InDels in two bitter gourd lines ‘47–2–1-1-3’ and ‘04–17,’ indicated that the InDel markers were reliable and accurate. To highlight their utilization, the InDel markers were employed to construct a genetic map using 113 ‘47–2–1-1-3’ × ‘04–17’ F2 individuals. This InDel genetic map of bitter gourd consisted of 164 new InDel markers distributed on 15 linkage groups with a coverage of approximately half of the genome. Conclusions This is the first report on the development of genome-wide InDel markers for bitter gourd. The validation of the amplification and genetic map construction suggests that these unique InDel markers may enhance the efficiency of genetic studies and marker-assisted selection for bitter gourd.

scholarly journals Modeling Linkage Disequilibrium and Identifying Recombination Hotspots Using Single-Nucleotide Polymorphism Data

Genetics ◽  
2003 ◽  
Vol 165 (4) ◽  
pp. 2213-2233 ◽  
Author(s):  
Na Li ◽  
Matthew Stephens
Keyword(s):  
Linkage Disequilibrium ◽  
Recombination Rate ◽  
Population Sample ◽  
Simulated Data ◽  
Region Of Interest ◽  
Population Data ◽  
Recombination Rates ◽  
Single Nucleotide ◽  
Recombination Hotspots ◽  
Genomic Regions

AbstractWe introduce a new statistical model for patterns of linkage disequilibrium (LD) among multiple SNPs in a population sample. The model overcomes limitations of existing approaches to understanding, summarizing, and interpreting LD by (i) relating patterns of LD directly to the underlying recombination process; (ii) considering all loci simultaneously, rather than pairwise; (iii) avoiding the assumption that LD necessarily has a “block-like” structure; and (iv) being computationally tractable for huge genomic regions (up to complete chromosomes). We examine in detail one natural application of the model: estimation of underlying recombination rates from population data. Using simulation, we show that in the case where recombination is assumed constant across the region of interest, recombination rate estimates based on our model are competitive with the very best of current available methods. More importantly, we demonstrate, on real and simulated data, the potential of the model to help identify and quantify fine-scale variation in recombination rate from population data. We also outline how the model could be useful in other contexts, such as in the development of more efficient haplotype-based methods for LD mapping.

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