3. 1930s Containment: Identity by State Dictate

2019 ◽  
pp. 115-150
Keyword(s):  
Identity By State

scholarly journals A likelihood ratio approach for identifying three-quarter siblings in genetic databases

Heredity ◽  
2021 ◽  
Author(s):  
Iván Galván-Femenía ◽  
Carles Barceló-Vidal ◽  
Lauro Sumoy ◽  
Victor Moreno ◽  
Rafael de Cid ◽  
...  
Keyword(s):  
Likelihood Ratio ◽  
Family Relationships ◽  
Genetic Research ◽  
Data Set ◽  
Scientific Disciplines ◽  
Genome Wide ◽  
Standard Quality ◽  
Control Procedures ◽  
Identity By State ◽  
Second Degree

AbstractThe detection of family relationships in genetic databases is of interest in various scientific disciplines such as genetic epidemiology, population and conservation genetics, forensic science, and genealogical research. Nowadays, screening genetic databases for related individuals forms an important aspect of standard quality control procedures. Relatedness research is usually based on an allele sharing analysis of identity by state (IBS) or identity by descent (IBD) alleles. Existing IBS/IBD methods mainly aim to identify first-degree relationships (parent–offspring or full siblings) and second degree (half-siblings, avuncular, or grandparent–grandchild) pairs. Little attention has been paid to the detection of in-between first and second-degree relationships such as three-quarter siblings (3/4S) who share fewer alleles than first-degree relationships but more alleles than second-degree relationships. With the progressively increasing sample sizes used in genetic research, it becomes more likely that such relationships are present in the database under study. In this paper, we extend existing likelihood ratio (LR) methodology to accurately infer the existence of 3/4S, distinguishing them from full siblings and second-degree relatives. We use bootstrap confidence intervals to express uncertainty in the LRs. Our proposal accounts for linkage disequilibrium (LD) by using marker pruning, and we validate our methodology with a pedigree-based simulation study accounting for both LD and recombination. An empirical genome-wide array data set from the GCAT Genomes for Life cohort project is used to illustrate the method.

scholarly journals Estimating relatedness between malaria parasites

2019 ◽  
Author(s):  
Aimee R. Taylor ◽  
Pierre E. Jacob ◽  
Daniel E. Neafsey ◽  
Caroline O. Buckee
Keyword(s):  
Genetic Epidemiology ◽  
Ad Hoc ◽  
Pathogen Transmission ◽  
Identity By Descent ◽  
Malaria Parasites ◽  
Data Set ◽  
Epidemiology Studies ◽  
Diverse Data ◽  
Prospective Study Design ◽  
Identity By State

1.AbstractUnderstanding the relatedness of individuals within or between populations is a common goal in biology. Increasingly, relatedness features in genetic epidemiology studies of pathogens. These studies are relatively new compared to those in humans and other organisms, but are important for designing interventions and understanding pathogen transmission. Only recently have researchers begun to routinely apply relatedness to apicomplexan eukaryotic malaria parasites, and to date have used a range of different approaches on an ad hoc basis. It remains unclear how to compare different studies, therefore, and which measures to use. Here, we systematically compare measures based on identity-by-state and identity-by-descent using a globally diverse data set of malaria parasites,Plasmodium falciparumandPlasmodium vivax, and provide marker requirements for estimates based on identity-by-descent. We formally show that the informativeness of polyallelic markers for relatedness inference is maximised when alleles are equifrequent. Estimates based on identity-by-state are sensitive to allele frequencies, which vary across populations and by experimental design. For portability across studies, we thus recommend estimates based on identity-by-descent. To generate reliable estimates, we recommend approximately 200 biallelic or 100 polyallelic markers. Confidence intervals illuminate inference across studies based on different sets of markers. These marker requirements, unlike many thus far reported, are immediately applicable to haploid malaria parasites and other haploid eukaryotes. This is the first attempt to provide rigorous analysis of the reliability of, and requirements for, relatedness inference in malaria genetic epidemiology, and will provide a basis for statistically informed prospective study design and surveillance strategies.

6. IDENTITY-BY-STATE BASED COMPREHENSIVE PGT: ADVANTAGES AND CHALLENGES

2019 ◽  
Vol 39 ◽  
pp. e30
Author(s):  
C. Melotte ◽  
J. Ding ◽  
E. Dimitriadou ◽  
O. Tsuiko ◽  
K. Van Den Bogaert ◽  
...  
Keyword(s):  
Identity By State

Comparison of identity by descent and identity by state for detecting genetic regions under selection in a sorghum pedigree breeding program

2005 ◽  
Vol 14 (4) ◽  
pp. 441-454 ◽  
Author(s):  
D. R. Jordan ◽  
Y. Z. Tao ◽  
I. D. Godwin ◽  
R. G. Henzell ◽  
M. Cooper ◽  
...  
Keyword(s):  
Breeding Program ◽  
Identity By Descent ◽  
Identity By State ◽  
Pedigree Breeding

scholarly journals Plasmodium falciparum genomic surveillance reveals spatial and temporal trends, association of genetic and physical distance, and household clustering

2020 ◽  
Author(s):  
Mouhamad Sy ◽  
Awa Deme ◽  
Joshua L. Warren ◽  
Rachel F. Daniels ◽  
Baba Dieye ◽  
...  
Keyword(s):  
Malaria Transmission ◽  
Malaria Control ◽  
Control Strategies ◽  
Temporal Trends ◽  
Genomic Data ◽  
Physical Distance ◽  
Genetic Types ◽  
Molecular Barcode ◽  
Spatial And Temporal Trends ◽  
Identity By State

ABSTRACTMolecular epidemiology using genomic data can help identify relationships between malaria parasite population structure, malaria transmission intensity, and ultimately help generate actionable data to assess the effectiveness of malaria control strategies. Genomic data, coupled with geographic information systems data, can further identify clusters or hotspots of malaria transmission, parasite genetic and spatial connectivity, and parasite movement by human or mosquito mobility over time and space. In this study, we performed longitudinal genomic surveillance in a cohort of 70 participants over four years from different neighborhoods and households in Thiès, Senegal—a region of exceptionally low malaria transmission (entomological inoculation rate (EIR) less than 1). Genetic identity (identity by state) was established using a 24 single nucleotide polymorphism molecular barcode and a multivariable linear regression model was used to establish genetic and spatial relationships. Our results show clustering of genetically similar parasites within households and a decline in genetic similarity of parasites with increasing distance. One household showed extremely high diversity and warrants further investigation as to the source of these diverse genetic types. This study illustrates the utility of genomic data with traditional epidemiological approaches for surveillance and detection of trends and patterns in malaria transmission not only by neighborhood but also by household. This approach can be implemented regionally and countrywide to strengthen and support malaria control and elimination efforts.

Inbreeding and Population Structure

2020 ◽  
pp. 47-74
Author(s):  
Daniel L. Hartl
Keyword(s):  
Population Structure ◽  
Recombinant Inbred ◽  
Recombinant Inbred Lines ◽  
Inbred Lines ◽  
Inbreeding Coefficient ◽  
Main Subject ◽  
Identity By Descent ◽  
Intimate Connection ◽  
Genotype Frequencies ◽  
Identity By State

Inbreeding and its consequences are the main subject of Chapter 3, beginning with the concepts of identity by descent versus identity by state, the inbreeding coefficient F, genotype frequencies with inbreeding, and calculation of the inbreeding coefficient from pedigrees. Inbreeding and heterosis are discussed along with the effects of inbreeding in humans and other organisms, regular systems of mating (selfing and partial selfing, sib mating), and the utility of recombinant inbred lines. The chapter emphasizes the intimate connection between inbreeding and hierarchical population structure as measured by the F-statistics.

scholarly journals A Log-Ratio Biplot Approach for Exploring Genetic Relatedness Based on Identity by State

2019 ◽  
Vol 10 ◽  
Author(s):  
Jan Graffelman ◽  
Iván Galván Femenía ◽  
Rafael de Cid ◽  
Carles Barceló Vidal
Keyword(s):  
Genetic Relatedness ◽  
Log Ratio ◽  
Identity By State

scholarly journals Haplotype-based inference of the distribution of fitness effects

Genetics ◽  
2022 ◽  
Author(s):  
Diego Ortega-Del Vecchyo ◽  
Kirk E Lohmueller ◽  
John Novembre
Keyword(s):  
Negative Selection ◽  
Low Frequency ◽  
Human Genetic Variation ◽  
Pairwise Identity ◽  
Fitness Effects ◽  
Sequencing Studies ◽  
Identity By State ◽  
Source Of Information ◽  
New Framework ◽  
New Mutations

Abstract Recent genome sequencing studies with large sample sizes in humans have discovered a vast quantity of low-frequency variants, providing an important source of information to analyze how selection is acting on human genetic variation. In order to estimate the strength of natural selection acting on low-frequency variants, we have developed a likelihood-based method that uses the lengths of pairwise identity-by-state between haplotypes carrying low-frequency variants. We show that in some non-equilibrium populations (such as those that have had recent population expansions) it is possible to distinguish between positive or negative selection acting on a set of variants. With our new framework, one can infer a fixed selection intensity acting on a set of variants at a particular frequency, or a distribution of selection coefficients for standing variants and new mutations. We show an application of our method to the UK10K phased haplotype dataset of individuals.

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