Benchmarking phasing software with a whole-genome sequenced cattle pedigree

Background: Accurate haplotype reconstruction is required in many applications in quantitative and population genomics. Different phasing methods are available but their accuracy must be evaluated for samples with different properties (population structure, marker density, etc.). We herein took advantage of whole-genome sequence data available for a Holstein cattle pedigree containing 264 individuals, including 98 trios, to evaluate several population-based phasing methods. This data represents a typical example of a livestock population, with low effective population size, high levels of relatedness and long-range linkage disequilibrium. Results: After stringent filtering of our sequence data, we evaluated several population-based phasing programs including one or more versions of AlphaPhase, ShapeIT, Beagle, Eagle and FImpute. To that end we used 98 individuals having both parents sequenced for validation. Their haplotypes reconstructed based on Mendelian segregation rules were considered the gold standard to assess the performance of population-based methods in two scenarios. In the first one, only these 98 individuals were phased, while in the second one, all the 264 sequenced individuals were phased simultaneously, ignoring the pedigree relationships. We assessed phasing accuracy based on switch error counts (SEC) and rates (SER), lengths of correctly phased haplotypes and pairwise SNP phasing accuracies (the probability that a pair of SNPs is correctly phased as a function of their distance). For most evaluated metrics or scenarios, the best software was either ShapeIT4.1 or Beagle5.2, both methods resulting in particularly high phasing accuracies. For instance, ShapeIT4.1 achieved a median SEC of 50 per individual and a mean haplotype block length of 24.1 Mb in the second scenario. These statistics are remarkable since the methods were evaluated with a map of 8,400,000 SNPs, and this corresponds to only one switch error every 40,000 phased informative markers. When more relatives were included in the data, FImpute3.0 reconstructed extremely long segments without errors. Conclusions: We report extremely high phasing accuracies in a typical livestock sample of 100 sequenced individuals. ShapeIT4.1 and Beagle5.2 proved to be the most accurate, particularly for phasing long segments. Nevertheless, most tools achieved high accuracy at short distances and would be suitable for applications requiring only local haplotypes.

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A comparative analysis of family-based and population-based association tests using whole genome sequence data

BMC Proceedings ◽

10.1186/1753-6561-8-s1-s33 ◽

2014 ◽

Vol 8 (Suppl 1) ◽

pp. S33 ◽

Cited By ~ 6

Author(s):

Jin J Zhou ◽

Wai-Ki Yip ◽

Michael H Cho ◽

Dandi Qiao ◽

Merry-Lynn N McDonald ◽

...

Keyword(s):

Comparative Analysis ◽

Genome Sequence ◽

Sequence Data ◽

Population Based ◽

Whole Genome Sequence ◽

Whole Genome ◽

Association Tests ◽

Genome Sequence Data ◽

Family Based

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Population genomics of East Asian ethnic groups

Hereditas ◽

10.1186/s41065-020-00162-w ◽

2020 ◽

Vol 157 (1) ◽

Author(s):

Ziqing Pan ◽

Shuhua Xu

Keyword(s):

Genetic Diversity ◽

East Asia ◽

Ethnic Groups ◽

Population Genomics ◽

Sequence Data ◽

East Asian ◽

Whole Genome Sequence ◽

Whole Genome ◽

Evolutionary Forces ◽

Asian Populations

AbstractEast Asia constitutes one-fifth of the global population and exhibits substantial genetic diversity. However, genetic investigations on populations in this region have been largely under-represented compared with European populations. Nonetheless, the last decade has seen considerable efforts and progress in genome-wide genotyping and whole-genome sequencing of the East-Asian ethnic groups. Here, we review the recent studies in terms of ancestral origin, population relationship, genetic differentiation, and admixture of major East- Asian groups, such as the Chinese, Korean, and Japanese populations. We mainly focus on insights from the whole-genome sequence data and also include the recent progress based on mitochondrial DNA (mtDNA) and Y chromosome data. We further discuss the evolutionary forces driving genetic diversity in East-Asian populations, and provide our perspectives for future directions on population genetics studies, particularly on underrepresented indigenous groups in East Asia.

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An evaluation of inbreeding measures using a whole-genome sequenced cattle pedigree

Heredity ◽

10.1038/s41437-020-00383-9 ◽

2020 ◽

Author(s):

Setegn Worku Alemu ◽

Naveen Kumar Kadri ◽

Chad Harland ◽

Pierre Faux ◽

Carole Charlier ◽

...

Keyword(s):

Sequence Data ◽

Intermediate Frequency ◽

Whole Genome Sequence ◽

Heterozygote Advantage ◽

Whole Genome ◽

Effective Population ◽

Deleterious Alleles ◽

Genomic Relationships ◽

Excess Homozygosity ◽

Small Effective Population Size

Abstract The estimation of the inbreeding coefficient (F) is essential for the study of inbreeding depression (ID) or for the management of populations under conservation. Several methods have been proposed to estimate the realized F using genetic markers, but it remains unclear which one should be used. Here we used whole-genome sequence data for 245 individuals from a Holstein cattle pedigree to empirically evaluate which estimators best capture homozygosity at variants causing ID, such as rare deleterious alleles or loci presenting heterozygote advantage and segregating at intermediate frequency. Estimators relying on the correlation between uniting gametes (FUNI) or on the genomic relationships (FGRM) presented the highest correlations with these variants. However, homozygosity at rare alleles remained poorly captured. A second group of estimators relying on excess homozygosity (FHOM), homozygous-by-descent segments (FHBD), runs-of-homozygosity (FROH) or on the known genealogy (FPED) was better at capturing whole-genome homozygosity, reflecting the consequences of inbreeding on all variants, and for young alleles with low to moderate frequencies (0.10 < . < 0.25). The results indicate that FUNI and FGRM might present a stronger association with ID. However, the situation might be different when recessive deleterious alleles reach higher frequencies, such as in populations with a small effective population size. For locus-specific inbreeding measures or at low marker density, the ranking of the methods can also change as FHBD makes better use of the information from neighboring markers. Finally, we confirmed that genomic measures are in general superior to pedigree-based estimates. In particular, FPED was uncorrelated with locus-specific homozygosity.

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Low coverage whole genome sequencing reveals the underlying structure of European sardine populations

10.22541/au.161628445.52373083/v1 ◽

2021 ◽

Author(s):

Rute da Fonseca ◽

Paula Campos ◽

Alba Rey de la Iglesia ◽

Gustavo Barroso ◽

Lucie Bergeron ◽

...

Keyword(s):

Population Genomics ◽

Sequence Data ◽

Eastern Mediterranean ◽

Whole Genome Sequence ◽

Underlying Structure ◽

Whole Genome ◽

Stock Management ◽

Data Set ◽

A Genome ◽

Low Coverage

Whole genome sequence data is an ideal tool for characterizing processes in ecology and evolution. Despite the lowering in sequencing costs, it can be challenging to produce a genome and high-coverage resequencing data for a non-model species. New population genomics data analysis pipelines based on genotype likelihoods allow for a significant reduction in cost by efficiently extracting information from low coverage sequence data. We demonstrate the robustness of such approaches with a genomic data set consisting of two draft genomes of the European sardine (Sardina pilchardus, Walbaum 1792), and resequencing data (~1.5 X depth) for 78 individuals from 12 sampling locations across the 5,000 Km of the species’ distribution range (from the Eastern Mediterranean to the archipelagos of Madeira and Azores). Our results clearly show at least three genetic clusters. One includes individuals from Azores and Madeira (two archipelagos in the Atlantic), the second corresponds to Iberia (the center of the sampling distribution), and the third gathers the Mediterranean samples and those from the Canary Islands. This suggests at least two important barriers to gene flow, even though these do not seem complete, with individuals from Iberia showing some degree of admixture. These results together with the genetic resources generated for this commercially important taxon provide a baseline for further studies aiming at identifying the nature of these barriers between Sardine populations, and information for transnational stock management of this highly exploited species towards sustainable fisheries.

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Faculty Opinions recommendation of Optimal algorithms for haplotype assembly from whole-genome sequence data.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.13339986.14707085 ◽

2011 ◽

Author(s):

Alejandro Schaffer

Keyword(s):

Genome Sequence ◽

Sequence Data ◽

Whole Genome Sequence ◽

Whole Genome ◽

Optimal Algorithms ◽

Genome Sequence Data ◽

Haplotype Assembly

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TIGER: inferring DNA replication timing from whole-genome sequence data

Bioinformatics ◽

10.1093/bioinformatics/btab166 ◽

2021 ◽

Cited By ~ 1

Author(s):

Amnon Koren ◽

Dashiell J Massey ◽

Alexa N Bracci

Keyword(s):

Dna Replication ◽

Genome Sequence ◽

Genomic Dna ◽

Sequence Data ◽

Replication Timing ◽

Whole Genome Sequence ◽

Supplementary Information ◽

Whole Genome ◽

Genome Sequence Data ◽

Dna Replication Timing

Abstract Motivation Genomic DNA replicates according to a reproducible spatiotemporal program, with some loci replicating early in S phase while others replicate late. Despite being a central cellular process, DNA replication timing studies have been limited in scale due to technical challenges. Results We present TIGER (Timing Inferred from Genome Replication), a computational approach for extracting DNA replication timing information from whole genome sequence data obtained from proliferating cell samples. The presence of replicating cells in a biological specimen leads to non-uniform representation of genomic DNA that depends on the timing of replication of different genomic loci. Replication dynamics can hence be observed in genome sequence data by analyzing DNA copy number along chromosomes while accounting for other sources of sequence coverage variation. TIGER is applicable to any species with a contiguous genome assembly and rivals the quality of experimental measurements of DNA replication timing. It provides a straightforward approach for measuring replication timing and can readily be applied at scale. Availability and Implementation TIGER is available at https://github.com/TheKorenLab/TIGER. Supplementary information Supplementary data are available at Bioinformatics online

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Whole genome sequence data of Bacillus australimaris strain B28A, isolated from Marine Water in India

Data in Brief ◽

10.1016/j.dib.2021.107240 ◽

2021 ◽

pp. 107240

Author(s):

Wael Ali Mohammed Hadi ◽

Boby T Edwin ◽

A Jayakumaran Nair

Keyword(s):

Genome Sequence ◽

Sequence Data ◽

Marine Water ◽

Whole Genome Sequence ◽

Whole Genome ◽

Genome Sequence Data

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Whole genome sequence data of Mycobacterium tuberculosis XDR strain, isolated from patient in Kazakhstan

Data in Brief ◽

10.1016/j.dib.2020.106416 ◽

2020 ◽

Vol 33 ◽

pp. 106416

Author(s):

Asset Daniyarov ◽

Askhat Molkenov ◽

Saule Rakhimova ◽

Ainur Akhmetova ◽

Zhannur Nurkina ◽

...

Keyword(s):

Mycobacterium Tuberculosis ◽

Genome Sequence ◽

Sequence Data ◽

Whole Genome Sequence ◽

Whole Genome ◽

Genome Sequence Data

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Population Genomics of American Mink Using Whole Genome Sequencing Data

Genes ◽

10.3390/genes12020258 ◽

2021 ◽

Vol 12 (2) ◽

pp. 258

Author(s):

Karim Karimi ◽

Duy Ngoc Do ◽

Mehdi Sargolzaei ◽

Younes Miar

Keyword(s):

Population Genomics ◽

Association Studies ◽

American Mink ◽

Population History ◽

Whole Genome Sequencing Data ◽

Whole Genome ◽

Nucleotide Polymorphisms ◽

Sequencing Data ◽

Effective Population ◽

Cross Validation Error

Characterizing the genetic structure and population history can facilitate the development of genomic breeding strategies for the American mink. In this study, we used the whole genome sequences of 100 mink from the Canadian Centre for Fur Animal Research (CCFAR) at the Dalhousie Faculty of Agriculture (Truro, NS, Canada) and Millbank Fur Farm (Rockwood, ON, Canada) to investigate their population structure, genetic diversity and linkage disequilibrium (LD) patterns. Analysis of molecular variance (AMOVA) indicated that the variation among color-types was significant (p < 0.001) and accounted for 18% of the total variation. The admixture analysis revealed that assuming three ancestral populations (K = 3) provided the lowest cross-validation error (0.49). The effective population size (Ne) at five generations ago was estimated to be 99 and 50 for CCFAR and Millbank Fur Farm, respectively. The LD patterns revealed that the average r2 reduced to <0.2 at genomic distances of >20 kb and >100 kb in CCFAR and Millbank Fur Farm suggesting that the density of 120,000 and 24,000 single nucleotide polymorphisms (SNP) would provide the adequate accuracy of genomic evaluation in these populations, respectively. These results indicated that accounting for admixture is critical for designing the SNP panels for genotype-phenotype association studies of American mink.

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