scholarly journals Tree House Explorer: A Novel Genome Browser for Phylogenomics

2022 ◽  
Author(s):  
Andrew J Harris ◽  
Nicole M Foley ◽  
Tiffani L Williams ◽  
William J Murphy
Keyword(s):  
Data Visualization ◽  
Genetic Divergence ◽  
Sliding Window ◽  
Genome Browser ◽  
Recombination Rates ◽  
Combined Analysis ◽  
Gene Annotations ◽  
Genome Wide ◽  
A Genome

Tree House Explorer (THEx) is a genome browser that integrates phylogenomic data and genomic annotations into a single interactive platform for combined analysis. THEx allows users to visualize genome-wide variation in evolutionary histories and genetic divergence on a chromosome-by-chromosome basis, with continuous sliding window comparisons to gene annotations, recombination rates, and other user-specified, highly customizable feature annotations. THEx provides a new platform for interactive phylogenomic data visualization to analyze and interpret the diverse evolutionary histories woven throughout genomes. Hosted on Conda, THEx integrates seamlessly into new or pre-existing workflows.

scholarly journals Predicting the Landscape of Recombination Using Deep Learning

2020 ◽  
Vol 37 (6) ◽  
pp. 1790-1808 ◽  
Author(s):  
Jeffrey R Adrion ◽  
Jared G Galloway ◽  
Andrew D Kern
Keyword(s):  
Deep Learning ◽  
Evolutionary History ◽  
Model Misspecification ◽  
Natural Populations ◽  
High Accuracy ◽  
Demographic Model ◽  
Recombination Rates ◽  
Genome Wide ◽  
A Genome ◽  
The Face

Abstract Accurately inferring the genome-wide landscape of recombination rates in natural populations is a central aim in genomics, as patterns of linkage influence everything from genetic mapping to understanding evolutionary history. Here, we describe recombination landscape estimation using recurrent neural networks (ReLERNN), a deep learning method for estimating a genome-wide recombination map that is accurate even with small numbers of pooled or individually sequenced genomes. Rather than use summaries of linkage disequilibrium as its input, ReLERNN takes columns from a genotype alignment, which are then modeled as a sequence across the genome using a recurrent neural network. We demonstrate that ReLERNN improves accuracy and reduces bias relative to existing methods and maintains high accuracy in the face of demographic model misspecification, missing genotype calls, and genome inaccessibility. We apply ReLERNN to natural populations of African Drosophila melanogaster and show that genome-wide recombination landscapes, although largely correlated among populations, exhibit important population-specific differences. Lastly, we connect the inferred patterns of recombination with the frequencies of major inversions segregating in natural Drosophila populations.

scholarly journals P822 Genetic analysis of ulcerative colitis in Japanese individuals using population-specific SNP array

2020 ◽  
Vol 14 (Supplement_1) ◽  
pp. S638-S639
Author(s):  
D Okamoto ◽  
Y Kakuta ◽  
N Takeo ◽  
R Moroi ◽  
M Kuroha ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
Japanese Population ◽  
Association Studies ◽  
Snp Array ◽  
Replication Study ◽  
Lower Probability ◽  
Genome Wide Association Studies ◽  
Combined Analysis ◽  
Genome Wide ◽  
A Genome

Abstract Background Previous genome wide association studies (GWASs) have identified over 200 susceptibility loci for inflammatory bowel diseases (IBD), but studies in non-European population are limited. To clarify the genetic background of ulcerative colitis (UC) in the Japanese population, we conducted GWAS using a population specific SNP array (Japonica Array). Methods Discovery GWAS included 624 UC patients and 2004 healthy controls (HC) and replication study included 1075 UC patients and 419 HCs. We performed GWAS using a Japonica Array and the subsequent imputation with a Japanese population reference panel (referred to as 2KJPN). After GWAS, significant and candidate loci were identified and the representative top SNPs of each region were analysed in replication study and combined analysis. The probability of colectomy between genotypes of rs117506082, the top hit SNP at HLA loci, was analysed using the Kaplan–Meier method. Results In the GWAS, only the HLA loci showed genome wide significant association [rs117506082, p = 6.69E−28, OR=1.29, 95%CI=1.23–1.35]. 7 regions with nominal significance included 2 known loci: IL23R [rs76418789, p = 6.29E−7, OR=0.89, 95%CI=0.85–0.93], IRF8 [rs16940202, p = 1.03E−6, OR=1.07, 95%CI=1.04–1.10] and 5 novel loci: miR-622 [rs9560575, p = 8.23E−7, OR=1.06, 95%CI=1.04–1.09], 14q31 [rs117618617, p = 1.53E−6, OR=1.13, 95%CI=1.09–1.19], KAT6B [rs12260609, p = 1.81E−6, OR=1.06, 95%CI=1.04–1.09], PAX3-CCDC140-SGPP2 [rs7589797, p = 2.87E−6, OR=0.94, 95%CI=0.93–0.97], KCNA2 [rs118020656, p = 4.01E−6, OR=1.12, 95%CI=1.07–1.18]. Combined analysis revealed that the HLA loci [rs117506082, p = 1.10E−23, OR=3.43, 95%CI=2.99–3.83] and IL23R p.G149R [rs76418789, p = 9.03E−11, OR=0.51, 95%CI=0.42–0.63] had a genome wide significant association. The GG genotype of rs117506082 had a significantly lower probability for total colectomy compared with the GA+AA genotype (p = 1.72E−2). Conclusion IL23R p.G149R is a susceptibility locus for UC in Japanese individuals. The GG genotype of rs117506082 at HLA loci, a risk genotype for UC susceptibility, may predict a better clinical course.

scholarly journals Inferring the landscape of recombination using recurrent neural networks

2019 ◽  
Author(s):  
Jeffrey R. Adrion ◽  
Jared G. Galloway ◽  
Andrew D. Kern
Keyword(s):  
Recurrent Neural Networks ◽  
Evolutionary History ◽  
Model Misspecification ◽  
Natural Populations ◽  
High Accuracy ◽  
Demographic Model ◽  
Recombination Rates ◽  
Genome Wide ◽  
A Genome ◽  
The Face

AbstractAccurately inferring the genome-wide landscape of recombination rates in natural populations is a central aim in genomics, as patterns of linkage influence everything from genetic mapping to understanding evolutionary history. Here we describe ReLERNN, a deep learning method for estimating a genome-wide recombination map that is accurate even with small numbers of pooled or individually sequenced genomes. Rather than use summaries of linkage disequilibrium as its input, ReLERNN takes columns from a genotype alignment, which are then modeled as a sequence across the genome using a recurrent neural network. We demonstrate that ReLERNN improves accuracy and reduces bias relative to existing methods and maintains high accuracy in the face of demographic model misspecification, missing genotype calls, and genome inaccessibility. We apply ReLERNN to natural populations of African Drosophila melanogaster and show that genome-wide recombination landscapes, while largely correlated among populations, exhibit important population-specific differences. Lastly, we connect the inferred patterns of recombination with the frequencies of major inversions segregating in natural Drosophila populations.

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.

Establishment of a genome-wide RNAi screen; Identification of novel genes involved in clonal maintenance of ALL

2014 ◽  
Vol 226 (03) ◽  
Author(s):  
F Ponthan ◽  
D Pal ◽  
J Vormoor ◽  
O Heidenreich
Keyword(s):  
Rnai Screen ◽  
Novel Genes ◽  
Genome Wide ◽  
A Genome

A genome-wide linkage scan for familial partial lipodystrophy susceptibility genes in a German kindreds

2007 ◽  
Vol 30 (4) ◽  
pp. 86
Author(s):  
M. Lanktree ◽  
J. Robinson ◽  
J. Creider ◽  
H. Cao ◽  
D. Carter ◽  
...  
Keyword(s):  
Subcutaneous Fat ◽  
Visceral Obesity ◽  
Fat Distribution ◽  
Dominant Negative ◽  
Molecular Forms ◽  
Partial Lipodystrophy ◽  
Genome Wide ◽  
A Genome ◽  
Familial Partial Lipodystrophy ◽  
Promoter Mutations

Background: In Dunnigan-type familial partial lipodystrophy (FPLD) patients are born with normal fat distribution, but subcutaneous fat from extremities and gluteal regions are lost during puberty. The abnormal fat distribution leads to the development of metabolic syndrome (MetS), a cluster of phenotypes including hyperglycemia, dyslipidemia, hypertension, and visceral obesity. The study of FPLD as a monogenic model of MetS may uncover genetic risk factors of the common MetS which affects ~30% of adult North Americans. Two molecular forms of FPLD have been identified including FPLD2, resulting from heterozygous mutations in the LMNA gene, and FPLD3, resulting from both heterozygous dominant negative and haploinsufficiency mutations in the PPARG gene. However, many patients with clinically diagnosed FPLD have no mutation in either LMNA or PPARG, suggesting the involvement of additional genes in FPLD etiology. Methods: Here, we report the results of an Affymetrix 10K GeneChip microarray genome-wide linkage analysis study of a German kindred displaying the FPLD phenotype and no known lipodystrophy-causing mutations. Results: The investigation identified three chromosomal loci, namely 1q, 3p, and 9q, with non-parametric logarithm of odds (NPL) scores >2.7. While not meeting the criteria for genome-wide significance, it is interesting to note that the 1q and 3p peaks contain the LMNA and PPARG genes respectively. Conclusions: Three possible conclusions can be drawn from these results: 1) the peaks identified are spurious findings, 2) additional genes physically close to LMNA, PPARG, or within 9q, are involved in FPLD etiology, or 3) alternative disease causing mechanisms not identified by standard exon sequencing approaches, such as promoter mutations, alternative splicing, or epigenetics, are also responsible for FPLD.

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