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Advances in Genetics 2008Association methods based on linkage disequilibrium (LD) offer a promising approach for detecting genetic variations that are responsible for complex human diseases.... (Review)
Review
Association methods based on linkage disequilibrium (LD) offer a promising approach for detecting genetic variations that are responsible for complex human diseases. Although methods based on individual single nucleotide polymorphisms (SNPs) may lead to significant findings, methods based on haplotypes comprising multiple SNPs on the same inherited chromosome may provide additional power for mapping disease genes and also provide insight on factors influencing the dependency among genetic markers. Such insights may provide information essential for understanding human evolution and also for identifying cis-interactions between two or more causal variants. Because obtaining haplotype information directly from experiments can be cost prohibitive in most studies, especially in large scale studies, haplotype analysis presents many unique challenges. In this chapter, we focus on two main issues: haplotype inference and haplotype-association analysis. We first provide a detailed review of methods for haplotype inference using unrelated individuals as well as related individuals from pedigrees. We then cover a number of statistical methods that employ haplotype information in association analysis. In addition, we discuss the advantages and limitations of different methods.
Topics: Genetic Techniques; Haplotypes; Humans; Models, Genetic; Pedigree
PubMed: 18358327
DOI: 10.1016/S0065-2660(07)00414-2 -
Trends in Genetics : TIG Nov 2022Complete pangenomics is crucial for understanding genetic diversity and evolution across the tree of life. Chromosome-scale, haplotype-resolved pangenomics allows...
Complete pangenomics is crucial for understanding genetic diversity and evolution across the tree of life. Chromosome-scale, haplotype-resolved pangenomics allows complex structural variations, long-range interactions, and associated functions to be discerned in species populations. We explore the need for high-resolution pangenomes, discuss computational strategies for their development, and describe applications in biodiversity and human health.
Topics: Chromosomes; Haplotypes; Humans
PubMed: 35817620
DOI: 10.1016/j.tig.2022.06.011 -
Plant Biotechnology Journal Jun 2022Genome phasing is a recently developed assembly method that separates heterozygous eukaryotic genomic regions and builds haplotype-resolved assemblies. Because... (Review)
Review
Genome phasing is a recently developed assembly method that separates heterozygous eukaryotic genomic regions and builds haplotype-resolved assemblies. Because differences between haplotypes are ignored in most published de novo genomes, assemblies are available as consensus genomes consisting of haplotype mixtures, thus increasing the need for genome phasing. Here, we review the operating principles and characteristics of several freely available and widely used phasing tools (TrioCanu, FALCON-Phase, and ALLHiC). An examination of downstream analyses using haplotype-resolved genome assemblies in plants indicated significant differences among haplotypes regarding chromosomal rearrangements, sequence insertions, and expression of specific alleles that contribute to the acquisition of the biological characteristics of plant species. Finally, we suggest directions to solve addressing limitations of current genome-phasing methods. This review provides insights into the current progress, limitations, and future directions of de novo genome phasing, which will enable researchers to easily access and utilize genome-phasing in studies involving highly heterozygous complex plant genomes.
Topics: Alleles; Genome, Plant; Genomics; Haplotypes; Plants; Sequence Analysis, DNA
PubMed: 35332665
DOI: 10.1111/pbi.13815 -
Frontiers in Bioscience (Scholar... Jan 2011Natural populations do not correspond to Mendelian populations. Effective populations are much smaller, inbreeding higher, and organization of large number of genes into... (Review)
Review
Natural populations do not correspond to Mendelian populations. Effective populations are much smaller, inbreeding higher, and organization of large number of genes into chromosomes connected with relatively low recombination rate invalidates the law of independent gene assortment. Under such conditions, a large number of genes is inherited as clusters and evolves as genetic units. Computer simulations have shown that mutations inside clusters are not eliminated independently by purifying selection but, instead, the whole clusters tend to complement each other. It means that whenever one haplotype carries one of two possible alleles, the other haplotype at that locus carries the other allele; thus inherited recessive deleterious diseases do not affect the health of the phenotype even if their fraction in the genome is high. This complementation seems to be a winning strategy in small or spatially distributed populations. We discuss possible consequences of this complementarity.
Topics: Computer Simulation; Genetics, Population; Haplotypes; Heterozygote; Humans; Inheritance Patterns; Models, Genetic; Mutation
PubMed: 21196385
DOI: 10.2741/s160 -
Molecular Ecology Mar 2023The term "haplotype block" is commonly used in the developing field of haplotype-based inference methods. We argue that the term should be defined based on the structure...
The term "haplotype block" is commonly used in the developing field of haplotype-based inference methods. We argue that the term should be defined based on the structure of the Ancestral Recombination Graph (ARG), which contains complete information on the ancestry of a sample. We use simulated examples to demonstrate key features of the relationship between haplotype blocks and ancestral structure, emphasizing the stochasticity of the processes that generate them. Even the simplest cases of neutrality or of a "hard" selective sweep produce a rich structure, often missed by commonly used statistics. We highlight a number of novel methods for inferring haplotype structure, based on the full ARG, or on a sequence of trees, and illustrate how they can be used to define haplotype blocks using an empirical data set. While the advent of new, computationally efficient methods makes it possible to apply these concepts broadly, they (and additional new methods) could benefit from adding features to explore haplotype blocks, as we define them. Understanding and applying the concept of the haplotype block will be essential to fully exploit long and linked-read sequencing technologies.
Topics: Haplotypes; Algorithms; Models, Genetic
PubMed: 36433653
DOI: 10.1111/mec.16793 -
Nature Biotechnology Sep 2022Routine haplotype-resolved genome assembly from single samples remains an unresolved problem. Here we describe an algorithm that combines PacBio HiFi reads and Hi-C...
Routine haplotype-resolved genome assembly from single samples remains an unresolved problem. Here we describe an algorithm that combines PacBio HiFi reads and Hi-C chromatin interaction data to produce a haplotype-resolved assembly without the sequencing of parents. Applied to human and other vertebrate samples, our algorithm consistently outperforms existing single-sample assembly pipelines and generates assemblies of similar quality to the best pedigree-based assemblies.
Topics: Diploidy; Genome; Haplotypes; High-Throughput Nucleotide Sequencing; Humans; Parents; Sequence Analysis, DNA
PubMed: 35332338
DOI: 10.1038/s41587-022-01261-x -
IEEE/ACM Transactions on Computational... 2022This article proposes a novel approach for Individual Human phasing through discovery of interesting hidden relations among single variant sites. The proposed framework,...
This article proposes a novel approach for Individual Human phasing through discovery of interesting hidden relations among single variant sites. The proposed framework, called ARHap, learns strong association rules among variant loci on the genome and develops a combinatorial approach for fast and accurate haplotype phasing based on the discovered associations. ARHap is composed of two main modules or processing phases. In the first phase, called association rule learning, ARHap identifies quantitative association rules from a collection of DNA reads of the organism under study, resulting in a set of strong rules that reveal the inter-dependency of alleles. In the next phase, called haplotype reconstruction, we develop algorithms to utilize the learned rules to construct highly reliable haplotypes at individual single nucleotide polymorphism (SNP) sites. ARHap has several features that lead to both fast and accurate haplotyping. It uses an incremental haplotype reconstruction approach that enables us to generate association rules according to the unreconstructed SNP sites during each round of the algorithm. During each round, the association rule learning module generates rules while constraining the length of the rules and limiting the rules to those that contribute to reconstruction of unreconstructed sites only. The framework begins by generating rules of small size and highly strong. The rule length can increase and/or criteria about strongness of the rule are adjusted gradually, during subsequent rounds, if some SNP sites have remained unreconstructed. This adaptive approach, which uses feedback from haplotype reconstruction module, eliminates generation of rules that do not contribute to haplotype reconstruction as well as weak rules that may introduce error in the final haplotypes. Extensive experimental analyses on datasets representing diploid organisms demonstrate superiority of ARHap in diploid haplotyping compared to the state-of-the-art algorithms. In particular, we show that this novel approach to haplotype phasing not only is fast but also achieves significantly better accuracy performance compared to other read-based computational approaches.
Topics: Humans; Haplotypes; Sequence Analysis, DNA; Algorithms; Polymorphism, Single Nucleotide; Alleles
PubMed: 34648456
DOI: 10.1109/TCBB.2021.3119955 -
Molecular Plant Mar 2022
Topics: Chromosomes; Genome; Haplotypes; Polymorphism, Single Nucleotide
PubMed: 35202865
DOI: 10.1016/j.molp.2022.02.010 -
Genes May 2022Signatures of positive selection in the genome are a characteristic mark of adaptation that can reveal an ongoing, recent, or ancient response to environmental change... (Review)
Review
Signatures of positive selection in the genome are a characteristic mark of adaptation that can reveal an ongoing, recent, or ancient response to environmental change throughout the evolution of a population. New sources of food, climate conditions, and exposure to pathogens are only some of the possible sources of selective pressure, and the rise of advantageous genetic variants is a crucial determinant of survival and reproduction. In this context, the ability to detect these signatures of selection may pinpoint genetic variants that are responsible for a significant change in gene regulation, gene expression, or protein synthesis, structure, and function. This review focuses on statistical methods that take advantage of linkage disequilibrium and haplotype determination to reveal signatures of positive selection in whole-genome sequencing data, showing that they emerge from different descriptions of the same underlying event. Moreover, considerations are provided around the application of these statistics to different species, their suitability for ancient DNA, and the usefulness of discovering variants under selection for biomedicine and public health in an evolutionary medicine framework.
Topics: Genome; Haplotypes; Linkage Disequilibrium; Selection, Genetic; Whole Genome Sequencing
PubMed: 35627311
DOI: 10.3390/genes13050926 -
Alzheimer's & Dementia : the Journal of... Dec 2016The MAPT H1 haplotype has been associated with several neurodegenerative diseases. We were interested in exploring the role of MAPT haplotypic variation in risk of... (Review)
Review
INTRODUCTION
The MAPT H1 haplotype has been associated with several neurodegenerative diseases. We were interested in exploring the role of MAPT haplotypic variation in risk of dementia with Lewy bodies (DLB).
METHOD
We genotyped six MAPT haplotype tagging SNPs and screened 431 clinical DLB cases, 347 pathologically defined high-likelihood DLB cases, and 1049 controls.
RESULT
We performed haplotypic association tests and detected an association with the protective H2 haplotype in our combined series (odds ratio [OR] = 0.75). We fine-mapped the locus and identified a relatively rare haplotype, H1G, that is associated with an increased risk of DLB (OR = 3.30, P = .0017). This association was replicated in our pathologically defined series (OR = 2.26, P = .035).
DISCUSSION
These results support a role for H1 and specifically H1G in susceptibility to DLB. However, the exact functional variant at the locus is still unknown, and additional studies are warranted to fully explain genetic risk of DLB at the MAPT locus.
Topics: Brain; Genetic Association Studies; Genetic Predisposition to Disease; Genotype; Haplotypes; Humans; Lewy Body Disease; Polymorphism, Single Nucleotide; tau Proteins
PubMed: 27287057
DOI: 10.1016/j.jalz.2016.05.002