scholarly journals Quantum Theory on Genome Evolution

2015 ◽  
Author(s):  
LiaoFu Luo
Keyword(s):  
Quantum Theory ◽  
Genome Evolution ◽  
Large Scale ◽  
Rapid Change ◽  
Classical Equation ◽  
Evolutionary Equation ◽  
Quantum Evolution ◽  
Time Dimension ◽  
Quantum Equation ◽  
A Genome

AbstractA model of genome evolution is proposed. Based on several general assumptions the evolutionary theory of a genome is formulated. Both the deterministic classical equation and the stochastic quantum equation are proposed. The classical equation is written in a form of of second-order differential equations on nucleotide frequencies varying in time. It is proved that the evolutionary equation can be put in a form of the least action principle and the latter can be used for obtaining the quantum generalization of the evolutionary law. The wave equation and uncertainty relation for the quantum evolution are deduced logically. Two fundamental constants of time dimension, the quantization constant and the evolutionary inertia, are introduced for characterizing the genome evolution. During speciation the large-scale rapid change of nucleotide frequency makes the evolutionary inertia of the dynamical variables of the genome largely decreasing or losing. That leads to the occurrence of quantum phase of the evolution. The observed smooth/sudden evolution is interpreted by the alternating occurrence of the classical and quantum phases. In this theory the probability of new-species formation is calculable from the first-principle. To deep the discussions we consider avian genome evolution as an example. More concrete forms on the assumed potential in fundamental equations, namely the diversity and the environmental potential, are introduced. Through the numerical calculations we found that the existing experimental data on avian macroevolution are consistent with our theory. Particularly, the law of the rapid post-Cretaceous radiation of neoavian birds can be understood in the quantum theory. Finally, the present work shows the quantum law may be more general than thought, since it plays key roles not only in atomic physics, but also in genome evolution.

Amphidiploid Brassica juncea contains conserved progenitor genomes

Genome ◽  
2000 ◽  
Vol 43 (4) ◽  
pp. 679-688 ◽  
Author(s):  
T Axelsson ◽  
C M Bowman ◽  
A G Sharpe ◽  
D J Lydiate ◽  
U Lagercrantz
Keyword(s):  
Genome Evolution ◽  
Fragment Length Polymorphism ◽  
Rapid Change ◽  
Linkage Maps ◽  
Diploid Progenitor ◽  
B Genome ◽  
Disomic Inheritance ◽  
Polyploid Formation ◽  
A Genome ◽  
Restriction Fragment Length

To perform a detailed study of genome evolution in the natural Brassica amphidiploid B. juncea, we have constructed two linkage maps based on RFLP (restriction fragment length polymorphism) markers; one generated from a cross between a resynthesized B. juncea (a chromosome doubled interspecific B. rapa × B. nigra hybrid) and a natural B. juncea cultivar, the other from a cross between two B. juncea cultivars. By using a common cultivar in both crosses, the two maps could be unambiguously integrated. All loci exhibited disomic inheritance of parental alleles in the natural × resynthesized cross, showing that B. rapa chromosomes paired exclusively with their A-genome homologues in B. juncea and that B. nigra chromosomes likewise paired with their B-genome homologues. The maps derived from the two crosses were also perfectly collinear. Furthermore, these maps were collinear with maps of the diploid progenitor species (B. nigra and B. rapa) produced using the same set of RFLP probes. These data indicate that the genome of B. juncea has remained essentially unchanged since polyploid formation. Our observations appear to refute the suggestion that the formation of polyploid genomes is accompanied by rapid change in genome structure.Key words: RFLP, comparative mapping, Brassica rapa, Brassica nigra, genome evolution.

scholarly journals Arabidopsis Genes Essential for Seedling Viability: Isolation of Insertional Mutants and Molecular Cloning

Genetics ◽  
2001 ◽  
Vol 159 (4) ◽  
pp. 1765-1778
Author(s):  
Gregory J Budziszewski ◽  
Sharon Potter Lewis ◽  
Lyn Wegrich Glover ◽  
Jennifer Reineke ◽  
Gary Jones ◽  
...  
Keyword(s):  
Large Scale ◽  
Protein Translocation ◽  
Gene Families ◽  
Mutant Phenotype ◽  
Lethal Mutant ◽  
A Genome ◽  
Genes Encoding ◽  
High Level ◽  
Mutant Lines ◽  
Genome Scale

Abstract We have undertaken a large-scale genetic screen to identify genes with a seedling-lethal mutant phenotype. From screening ~38,000 insertional mutant lines, we identified >500 seedling-lethal mutants, completed cosegregation analysis of the insertion and the lethal phenotype for >200 mutants, molecularly characterized 54 mutants, and provided a detailed description for 22 of them. Most of the seedling-lethal mutants seem to affect chloroplast function because they display altered pigmentation and affect genes encoding proteins predicted to have chloroplast localization. Although a high level of functional redundancy in Arabidopsis might be expected because 65% of genes are members of gene families, we found that 41% of the essential genes found in this study are members of Arabidopsis gene families. In addition, we isolated several interesting classes of mutants and genes. We found three mutants in the recently discovered nonmevalonate isoprenoid biosynthetic pathway and mutants disrupting genes similar to Tic40 and tatC, which are likely to be involved in chloroplast protein translocation. Finally, we directly compared T-DNA and Ac/Ds transposon mutagenesis methods in Arabidopsis on a genome scale. In each population, we found only about one-third of the insertion mutations cosegregated with a mutant phenotype.

scholarly journals Genetic variation in recombination rate in the pig

2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Martin Johnsson ◽  
Andrew Whalen ◽  
Roger Ros-Freixedes ◽  
Gregor Gorjanc ◽  
Ching-Yi Chen ◽  
...  
Keyword(s):  
Genetic Variation ◽  
Recombination Rate ◽  
Large Scale ◽  
Genome Wide Association Study ◽  
Genetic Material ◽  
A Genome ◽  
Pig Genome ◽  
Genetic Length ◽  
Trait Locus ◽  
Genomic Regions

Abstract Background Meiotic recombination results in the exchange of genetic material between homologous chromosomes. Recombination rate varies between different parts of the genome, between individuals, and is influenced by genetics. In this paper, we assessed the genetic variation in recombination rate along the genome and between individuals in the pig using multilocus iterative peeling on 150,000 individuals across nine genotyped pedigrees. We used these data to estimate the heritability of recombination and perform a genome-wide association study of recombination in the pig. Results Our results confirmed known features of the recombination landscape of the pig genome, including differences in genetic length of chromosomes and marked sex differences. The recombination landscape was repeatable between lines, but at the same time, there were differences in average autosome-wide recombination rate between lines. The heritability of autosome-wide recombination rate was low but not zero (on average 0.07 for females and 0.05 for males). We found six genomic regions that are associated with recombination rate, among which five harbour known candidate genes involved in recombination: RNF212, SHOC1, SYCP2, MSH4 and HFM1. Conclusions Our results on the variation in recombination rate in the pig genome agree with those reported for other vertebrates, with a low but nonzero heritability, and the identification of a major quantitative trait locus for recombination rate that is homologous to that detected in several other species. This work also highlights the utility of using large-scale livestock data to understand biological processes.

scholarly journals Systematic Detection of Large-Scale Multi-Gene Horizontal Transfer in Prokaryotes

2021 ◽  
Author(s):  
Lina Kloub ◽  
Sean Gosselin ◽  
Matthew Fullmer ◽  
Joerg Graf ◽  
J Peter Gogarten ◽  
...  
Keyword(s):  
Gene Transfer ◽  
Large Scale ◽  
Single Gene ◽  
Gene Families ◽  
Microbial Evolution ◽  
Phylogenetic Distance ◽  
Secretion Systems ◽  
Type Iii Secretion Systems ◽  
A Genome ◽  
Conserved Gene

Abstract Horizontal gene transfer (HGT) is central to prokaryotic evolution. However, little is known about the “scale” of individual HGT events. In this work, we introduce the first computational framework to help answer the following fundamental question: How often does more than one gene get horizontally transferred in a single HGT event? Our method, called HoMer, uses phylogenetic reconciliation to infer single-gene HGT events across a given set of species/strains, employs several techniques to account for inference error and uncertainty, combines that information with gene order information from extant genomes, and uses statistical analysis to identify candidate horizontal multi-gene transfers (HMGTs) in both extant and ancestral species/strains. HoMer is highly scalable and can be easily used to infer HMGTs across hundreds of genomes. We apply HoMer to a genome-scale dataset of over 22000 gene families from 103 Aeromonas genomes and identify a large number of plausible HMGTs of various scales at both small and large phylogenetic distances. Analysis of these HMGTs reveals interesting relationships between gene function, phylogenetic distance, and frequency of multi-gene transfer. Among other insights, we find that (i) the observed relative frequency of HMGT increases as divergence between genomes increases, (ii) HMGTs often have conserved gene functions, and (iii) rare genes are frequently acquired through HMGT. We also analyze in detail HMGTs involving the zonula occludens toxin and type III secretion systems. By enabling the systematic inference of HMGTs on a large scale, HoMer will facilitate a more accurate and more complete understanding of HGT and microbial evolution.

Imaging and Cognitive Genetics: The Norwegian Cognitive NeuroGenetics Sample

2012 ◽  
Vol 15 (3) ◽  
pp. 442-452 ◽  
Author(s):  
Thomas Espeseth ◽  
Andrea Christoforou ◽  
Astri J. Lundervold ◽  
Vidar M. Steen ◽  
Stephanie Le Hellard ◽  
...  
Keyword(s):  
Sample Size ◽  
Cognitive Aging ◽  
Brain Function ◽  
Large Scale ◽  
Adult Life ◽  
Aging Brain ◽  
Adult Life Span ◽  
Cross Sectional ◽  
A Genome ◽  
Effects Of Aging

Data collection for the Norwegian Cognitive NeuroGenetics sample (NCNG) was initiated in 2003 with a research grant (to Ivar Reinvang) to study cognitive aging, brain function, and genetic risk factors. The original focus was on the effects of aging (from middle age and up) and candidate genes (e.g., APOE, CHRNA4) in cross-sectional and longitudinal designs, with the cognitive and MRI-based data primarily being used for this purpose. However, as the main topic of the project broadened from cognitive aging to imaging and cognitive genetics more generally, the sample size, age range of the participants, and scope of available phenotypes and genotypes, have developed beyond the initial project. In 2009, a genome-wide association (GWA) study was undertaken, and the NCNG proper was established to study the genetics of cognitive and brain function more comprehensively. The NCNG is now controlled by the NCNG Study Group, which consists of the present authors. Prominent features of the NCNG are the adult life-span coverage of healthy participants with high-dimensional imaging, and cognitive data from a genetically homogenous sample. Another unique property is the large-scale (sample size 300–700) use of experimental cognitive tasks focusing on attention and working memory. The NCNG data is now used in numerous ongoing GWA-based studies and has contributed to several international consortia on imaging and cognitive genetics. The objective of the following presentation is to give other researchers the information necessary to evaluate possible contributions from the NCNG to various multi-sample data analyses.

Reflections on Medical Technology as a Special Type of Capital

1987 ◽  
Vol 3 (2) ◽  
pp. 275-280
Author(s):  
Mark G. Field
Keyword(s):  
Health Care ◽  
Health Services ◽  
Medical Technology ◽  
Classical Equation ◽  
Hospital Services ◽  
Time Dimension ◽  
Goods And Services ◽  
Use Of Technology ◽  
Health Field

AbstractThe classical equation for the production of goods and services, that is, the combination of labor, capital, and knowledge, constrained by the time dimension, may also be used to examine the production of medical and hospital services. However, this is qualified by the special nature of the “capital” used in health care, particularly medical technology. Because of the particular nature of health services, the adoption and the use of technology follows rules that are different from those in the industrial sphere. These differences are examined in some detail as are the implications for the health field in general, and for the hospitals where most of the new (and often costly) technology is located.

An International Campaign for Agricultural and Livestock Genomics (CALG)

2002 ◽  
Vol 06 (24) ◽  
pp. 958-965
Author(s):  
Jun Yu ◽  
Jian Wang ◽  
Huanming Yang
Keyword(s):  
Large Scale ◽  
Cost Effective ◽  
Model Organisms ◽  
Environmental Biology ◽  
Cdna Sequences ◽  
Governmental Agencies ◽  
Technology Innovations ◽  
A Genome ◽  
Starting Point ◽  
The Cost

A coordinated international effort to sequence agricultural and livestock genomes has come to its time. While human genome and genomes of many model organisms (related to human health and basic biological interests) have been sequenced or plugged in the sequencing pipelines, agronomically important crop and livestock genomes have not been given high enough priority. Although we are facing many challenges in policy-making, grant funding, regional task emphasis, research community consensus and technology innovations, many initiatives are being announced and formulated based on the cost-effective and large-scale sequencing procedure, known as whole genome shotgun (WGS) sequencing that produces draft sequences covering a genome from 95 percent to 99 percent. Identified genes from such draft sequences, coupled with other resources, such as molecular markers, large-insert clones and cDNA sequences, provide ample information and tools to further our knowledge in agricultural and environmental biology in the genome era that just comes to its accelerated period. If the campaign succeeds, molecular biologists, geneticists and field biologists from all countries, rich or poor, would be brought to the same starting point and expect another astronomical increase of basic genomic information, ready to convert effectively into knowledge that will ultimately change our lives and environment into a greater and better future. We call upon national and international governmental agencies and organizations as well as research foundations to support this unprecedented movement.

scholarly journals SkewIT: The Skew Index Test for large-scale GC Skew analysis of bacterial genomes

2020 ◽  
Vol 16 (12) ◽  
pp. e1008439
Author(s):  
Jennifer Lu ◽  
Steven L. Salzberg
Keyword(s):  
Large Scale ◽  
Analysis Tool ◽  
Index Test ◽  
Bacterial Genomes ◽  
Phylogenetic Groups ◽  
Bacterial Phyla ◽  
Link Type ◽  
Gc Skew ◽  
A Genome ◽  
Web App

GC skew is a phenomenon observed in many bacterial genomes, wherein the two replication strands of the same chromosome contain different proportions of guanine and cytosine nucleotides. Here we demonstrate that this phenomenon, which was first discovered in the mid-1990s, can be used today as an analysis tool for the 15,000+ complete bacterial genomes in NCBI’s Refseq library. In order to analyze all 15,000+ genomes, we introduce a new method, SkewIT (Skew Index Test), that calculates a single metric representing the degree of GC skew for a genome. Using this metric, we demonstrate how GC skew patterns are conserved within certain bacterial phyla, e.g. Firmicutes, but show different patterns in other phylogenetic groups such as Actinobacteria. We also discovered that outlier values of SkewIT highlight potential bacterial mis-assemblies. Using our newly defined metric, we identify multiple mis-assembled chromosomal sequences in previously published complete bacterial genomes. We provide a SkewIT web app https://jenniferlu717.shinyapps.io/SkewIT/ that calculates SkewI for any user-provided bacterial sequence. The web app also provides an interactive interface for the data generated in this paper, allowing users to further investigate the SkewI values and thresholds of the Refseq-97 complete bacterial genomes. Individual scripts for analysis of bacterial genomes are provided in the following repository: https://github.com/jenniferlu717/SkewIT.

scholarly journals SINE jumping contributes to large-scale polymorphisms in the pig genomes

2021 ◽  
Author(s):  
Cai Chen ◽  
Enrico D'Alessandro ◽  
Eduard Murani ◽  
Yao Zheng ◽  
Domenico Giosa ◽  
...  
Keyword(s):  
Genetic Analysis ◽  
Population Genetic ◽  
Large Scale ◽  
Structural Variations ◽  
Population Genetic Analysis ◽  
Protein Coding ◽  
Pig Breeds ◽  
A Genome ◽  
Trait Locus ◽  
And Cluster Analysis

Abstract Background: Molecular markers based on retrotransposon insertion polymorphisms (RIPs) have been developed and are widely used in plants and animals. Short interspersed nuclear elements (SINEs) exert wide impacts on gene activity and even on phenotypes. However, SINE RIP profiles in livestock remain largely unknown, and not be revealed in pigs. Results: Our data revealed that SINEA1 displayed the most polymorphic insertions (22.5% intragenic and 26.5% intergenic), followed by SINEA2 (10.5% intragenic and 9% intergenic) and SINEA3 (12.5% intragenic and 5.0% intergenic). We developed a genome-wide SINE RIP mining protocol and obtained a large number of SINE RIPs (36,284), with over 80% accuracy and an even distribution in chromosomes (14.5/Mb), and 74.34% of SINE RIPs generated by SINEA1 element. Over 65% of pig SINE RIPs overlap with genes, with significant enrichment in the first and second introns of protein-coding and long non-coding RNA genes. Nearly half of the RIPs are common in these pig breeds. Sixteen SINE RIPs were applied for population genetic analysis in 23 pig breeds, the phylogeny tree and cluster analysis were generally consistent with the geographical distributions of native pig breeds in China. Conclusions: Our analysis revealed that SINEA1–3 elements, particularly SINEA1, are high polymorphic across different pig breeds, and generate large-scale structural variations in the pig genomes. And over 35, 000 SINE RIP markers were obtained. These data indicate that young SINE elements play important roles in creating new genetic variations and shaping the evolution of pig genome, and also provide strong evidences to support the great potential of SINE RIPs as genetic markers, which can be used for population genetic analysis and quantitative trait locus (QTL) mapping in pig.

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