Estimating IBD tracts from low coverage NGS data

Vieira, Filipe Garrett; Albrechtsen, Anders; Nielsen, Rasmus

doi:10.1093/bioinformatics/btw212

Cited by 41 publications

(69 citation statements)

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“…() and Vieira et al. () (note that the model by Narasimhan et al. () does not estimate the rate but a single‐transition parameters combining R and the genetic distances) and results in better estimates of the rate.…”

Section: Discussionmentioning

confidence: 99%

“…In these studies, the transition rate R determines the rate of change between the two states in units of genetic distance (Thompson, ) and is such that mean length of HBD and non‐HBD segments are equal to

1 / (R (1 - ρ))

and

1 / (R ρ)

, respectively (Leutenegger et al., ). Although this rate depends on time to common ancestor(s) (Vieira et al., ), it is not equal to the generational age of HBD as illustrated by Leutenegger et al. () and Leutenegger, Sahbatou, Gazal, Cann, and Genin () for a few examples.…”

Section: The Modelsmentioning

confidence: 99%

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A model‐based approach to characterize individual inbreeding at both global and local genomic scales

2017

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Inbreeding results from the mating of related individuals and may be associated with reduced fitness because it brings together deleterious variants in one individual. In general, inbreeding is estimated with respect to an arbitrary base population consisting of ancestors that are assumed unrelated. We herein propose a model-based approach to estimate and characterize individual inbreeding at both global and local genomic scales by assuming the individual genome is a mosaic of homozygous-by-descent (HBD) and non-HBD segments. The HBD segments may originate from ancestors tracing back to different periods in the past defining distinct age-related classes. The lengths of the HBD segments are exponentially distributed with class-specific parameters reflecting that inbreeding of older origin generates on average shorter stretches of observed homozygous markers. The model is implemented in a hidden Markov model framework that uses marker allele frequencies, genetic distances, genotyping error rates and the sequences of observed genotypes. Note that genotyping errors, low-fold sequencing or genotype-by-sequencing data are easily accommodated under this framework. Based on simulations under the inference model, we show that the genomewide inbreeding coefficients and the parameters of the model are accurately estimated. In addition, when several inbreeding classes are simulated, the model captures them if their ages are sufficiently different. Complementary analyses, either on data sets simulated under more realistic models or on human, dog and sheep real data, illustrate the range of applications of the approach and how it can reveal recent demographic histories among populations (e.g., very recent bottlenecks or founder effects). The method also allows to clearly identify individuals resulting from extreme consanguineous matings.

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Section: Discussionmentioning

confidence: 99%

1 / (R (1 - ρ))

and

1 / (R ρ)

Section: The Modelsmentioning

confidence: 99%

A model‐based approach to characterize individual inbreeding at both global and local genomic scales

2017

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“…To our knowledge no study has thus far (June 2017) used the lcWGR approach for the study of inbreeding depression in wild populations, however, this method has been successful in the identification of causal mutations of three phenotypic traits in inbred rice varieties (Wang, Xu, et al, ) and the estimation of individual inbreeding coefficients (Vieira, Fumagalli, Albrechtsen, & Nielsen, ; Vieira et al. ). Thus, we envision lcWGR data is likely to be useful for this purpose in the near future.…”

Section: Applications Of Wgr In Conservation and Managementmentioning

confidence: 99%

Whole‐genome sequencing approaches for conservation biology: Advantages, limitations and practical recommendations

2017

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Whole-genome resequencing (WGR) is a powerful method for addressing fundamental evolutionary biology questions that have not been fully resolved using traditional methods. WGR includes four approaches: the sequencing of individuals to a high depth of coverage with either unresolved or resolved haplotypes, the sequencing of population genomes to a high depth by mixing equimolar amounts of unlabelled-individual DNA (Pool-seq) and the sequencing of multiple individuals from a population to a low depth (lcWGR). These techniques require the availability of a reference genome. This, along with the still high cost of shotgun sequencing and the large demand for computing resources and storage, has limited their implementation in nonmodel species with scarce genomic resources and in fields such as conservation biology. Our goal here is to describe the various WGR methods, their pros and cons and potential applications in conservation biology. WGR offers an unprecedented marker density and surveys a wide diversity of genetic variations not limited to single nucleotide polymorphisms (e.g., structural variants and mutations in regulatory elements), increasing their power for the detection of signatures of selection and local adaptation as well as for the identification of the genetic basis of phenotypic traits and diseases. Currently, though, no single WGR approach fulfils all requirements of conservation genetics, and each method has its own limitations and sources of potential bias. We discuss proposed ways to minimize such biases. We envision a not distant future where the analysis of whole genomes becomes a routine task in many nonmodel species and fields including conservation biology.

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“…The large uncertainties of such called SNP genotypes mean that erroneous results could be produced, such as an overestimation of inbreeding (Vieira et al, 2013) and biased estimates of relatedness (Vieira et al, 2016).…”

Section: Quality Controlmentioning

confidence: 99%

“…By using genotype likelihoods to account for uncertainties at individual genotype level, an appropriately designed program can yield unbiased and accurate estimates of parameters such as inbreeding and relatedness (Vieira et al, 2013(Vieira et al, , 2016, even when the average coverage is very low and thus the genotype data are highly uncertain (Buerkle & Gompert, 2013). Buerkle & Gompert (2013) show that partitioning the sequencing effort maximally among individuals and obtaining approximately one read per locus and individual (1X coverage) yields the most information about a population.…”

Section: Quality Controlmentioning

confidence: 99%

Genetic and genomic monitoring with minimally invasive sampling methods

Carroll

Bruford

DeWoody

et al. 2017

Preprint

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Emerging genomic technologies are reshaping the field of molecular ecology. However, many modern genomic approaches (e.g., RAD-seq) require large amounts of high quality template DNA. This poses a problem for an active branch of conservation biology: genetic monitoring using minimally invasive sampling (MIS) methods. Without handling or even observing an animal, MIS methods (e.g. collection of hair, skin, faeces) can provide genetic information on individuals or populations. Such samples typically yield low quality and/or quantities of DNA, restricting the type of molecular methods that can be used. Despite this limitation, genetic monitoring using MIS is an effective tool for estimating population demographic parameters and monitoring genetic diversity in natural populations. Genetic monitoring is likely to become more important in the future as many natural populations are undergoing anthropogenically-driven declines, which are unlikely to abate without intensive management efforts that often include MIS approaches. Here we profile the expanding suite of genomic methods and platforms compatible with producing genotypes from MIS, considering factors such as development costs and error rates. We evaluate how powerful new approaches will enhance our ability to investigate questions typically answered using genetic monitoring, such as estimating abundance, genetic structure and relatedness. As the field is in a period of unusually rapid transition, we also highlight the importance of legacy datasets and recommend how to address the challenges of moving between traditional and next generation genetic monitoring platforms. Finally, we consider how genetic monitoring could move beyond genotypes in the future. For example, assessing microbiomes or epigenetic markers could provide a greater understanding of the relationship between individuals and their environment.PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.3209v1 | CC BY 4.0 Open Access |

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Estimating IBD tracts from low coverage NGS data

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 41 publications

References 41 publications

A model‐based approach to characterize individual inbreeding at both global and local genomic scales

A model‐based approach to characterize individual inbreeding at both global and local genomic scales

Whole‐genome sequencing approaches for conservation biology: Advantages, limitations and practical recommendations

Genetic and genomic monitoring with minimally invasive sampling methods

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