An evaluation of inbreeding measures using a whole-genome sequenced cattle pedigree.
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ABSTRACT:
SUBMITTER: Alemu SW
PROVIDER: S-EPMC8027009 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundAccurate 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.ResultsAfter 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 the probability that there is no phasing error between a pair of SNPs 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 (scenario 2). 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 (scenario 2), FImpute3.0 reconstructed extremely long segments without errors.ConclusionsWe report extremely high phasing accuracies in a typical livestock sample. ShapeIT4.1 and Beagle5.2 proved to be the most accurate, particularly for phasing long segments and in the first scenario. Nevertheless, most tools achieved high accuracy at short distances and would be suitable for applications requiring only local haplotypes.
| S-EPMC8845340 | biostudies-literature
Project description:Levels of inbreeding in cattle populations have increased in the past due to the use of a limited number of bulls for artificial insemination. High levels of inbreeding lead to reduced genetic diversity and inbreeding depression. Various estimators based on different sources, e.g., pedigree or genomic data, have been used to estimate inbreeding coefficients in cattle populations. However, the comparative advantage of using full sequence data to assess inbreeding is unknown. We used pedigree and genomic data at different densities from 50k to full sequence variants to compare how different methods performed for the estimation of inbreeding levels in three different cattle breeds.Five different estimates for inbreeding were calculated and compared in this study: pedigree based inbreeding coefficient (F(PED)); run of homozygosity (ROH)-based inbreeding coefficients (F(ROH)); genomic relationship matrix (GRM)-based inbreeding coefficients (F(GRM)); inbreeding coefficients based on excess of homozygosity (F(HOM)) and correlation of uniting gametes (F(UNI)). Estimates using ROH provided the direct estimated levels of autozygosity in the current populations and are free effects of allele frequencies and incomplete pedigrees which may increase in inaccuracy in estimation of inbreeding. The highest correlations were observed between F(ROH) estimated from the full sequence variants and the F(ROH) estimated from 50k SNP (single nucleotide polymorphism) genotypes. The estimator based on the correlation between uniting gametes (F(UNI)) using full genome sequences was also strongly correlated with F(ROH) detected from sequence data.Estimates based on ROH directly reflected levels of homozygosity and were not influenced by allele frequencies, unlike the three other estimates evaluated (F(GRM), F(HOM) and FU(NI)), which depended on estimated allele frequencies. F(PED) suffered from limited pedigree depth. Marker density affects ROH estimation. Detecting ROH based on 50k chip data was observed to give estimates similar to ROH from sequence data. In the absence of full sequence data ROH based on 50k can be used to access homozygosity levels in individuals. However, genotypes denser than 50k are required to accurately detect short ROH that are most likely identical by descent (IBD).
| S-EPMC4509611 | biostudies-literature
Project description:This study evaluated the accuracy of sequence imputation in Hanwoo beef cattle using different reference panels: a large multi-breed reference with no Hanwoo (n = 6269), a much smaller Hanwoo purebred reference (n = 88), and both datasets combined (n = 6357). The target animals were 136 cattle both sequenced and genotyped with the Illumina BovineSNP50 v2 (50K). The average imputation accuracy measured by the Pearson correlation (R) was 0.695 with the multi-breed reference, 0.876 with the purebred Hanwoo, and 0.887 with the combined data; the average concordance rates (CR) were 88.16%, 94.49%, and 94.84%, respectively. The accuracy gains from adding a large multi-breed reference of 6269 samples to only 88 Hanwoo was marginal; however, the concordance rate for the heterozygotes decreased from 85% to 82%, and the concordance rate for fixed SNPs in Hanwoo also decreased from 99.98% to 98.73%. Although the multi-breed panel was large, it was not sufficiently representative of the breed for accurate imputation without the Hanwoo animals. Additionally, we evaluated the value of high-density 700K genotypes (n = 991) as an intermediary step in the imputation process. The imputation accuracy differences were negligible between a single-step imputation strategy from 50K directly to sequence and a two-step imputation approach (50K-700K-sequence). We also observed that imputed sequence data can be used as a reference panel for imputation (mean R = 0.9650, mean CR = 98.35%). Finally, we identified 31 poorly imputed genomic regions in the Hanwoo genome and demonstrated that imputation accuracies were particularly lower at the chromosomal ends.
| S-EPMC9454883 | biostudies-literature
Project description:The inbreeding coefficient (F) of individuals can be estimated from molecular marker data, such as SNPs, using measures of homozygosity of individual markers or runs of homozygosity (ROH) across the genome. These different measures of F can then be used to estimate the rate of inbreeding depression (ID) for quantitative traits. Some recent simulation studies have investigated the accuracy of this estimation with contradictory results. Whereas some studies suggest that estimates of inbreeding from ROH account more accurately for ID, others suggest that inbreeding measures from SNP-by-SNP homozygosity giving a large weight to rare alleles are more accurate. Here, we try to give more light on this issue by carrying out a set of computer simulations considering a range of population genetic parameters and population sizes. Our results show that the previous studies are indeed not contradictory. In populations with low effective size, where relationships are more tight and selection is relatively less intense, F measures based on ROH provide very accurate estimates of ID whereas SNP-by-SNP-based F measures with high weight to rare alleles can show substantial upwardly biased estimates of ID. However, in populations of large effective size, with more intense selection and trait allele frequencies expected to be low if they are deleterious for fitness because of purifying selection, average estimates of ID from SNP-by-SNP-based F values become unbiased or slightly downwardly biased and those from ROH-based F values become slightly downwardly biased. The noise attached to all these estimates, nevertheless, can be very high in large-sized populations. We also investigate the relationship between the different F measures and the homozygous mutation load, which has been suggested as a proxy of inbreeding depression.
| S-EPMC7896712 | biostudies-literature
Project description:BackgroundInbreeding depression refers to the decrease in mean performance due to inbreeding. Inbreeding depression is caused by an increase in homozygosity and reduced expression of (on average) favourable dominance effects. Dominance effects and allele frequencies differ across loci, and consequently inbreeding depression is expected to differ along the genome. In this study, we investigated differences in inbreeding depression across the genome of Dutch Holstein Friesian cattle, by estimating dominance effects and effects of regions of homozygosity (ROH).MethodsGenotype (75 k) and phenotype data of 38,792 cows were used. For nine yield, fertility and udder health traits, GREML models were run to estimate genome-wide inbreeding depression and estimate additive, dominance and ROH variance components. For this purpose, we introduced a ROH-based relationship matrix. Additive, dominance and ROH effects per SNP were obtained through back-solving. In addition, a single SNP GWAS was performed to identify significant additive, dominance or ROH associations.ResultsGenome-wide inbreeding depression was observed for all yield, fertility and udder health traits. For example, a 1% increase in genome-wide homozygosity was associated with a decrease in 305-d milk yield of approximately 99 kg. For yield traits only, including dominance and ROH effects in the GREML model resulted in a better fit (P < 0.05) than a model with only additive effects. After correcting for the effect of genome-wide homozygosity, dominance and ROH variance explained less than 1% of the phenotypic variance for all traits. Furthermore, dominance and ROH effects were distributed evenly along the genome. The most notable region with a favourable dominance effect for yield traits was on chromosome 5, but overall few regions with large favourable dominance effects and significant dominance associations were detected. No significant ROH-associations were found.ConclusionsInbreeding depression was distributed quite equally along the genome and was well captured by genome-wide homozygosity. These findings suggest that, based on 75 k SNP data, there is little benefit of accounting for region-specific inbreeding depression in selection schemes.
| S-EPMC7594306 | biostudies-literature
Project description:In this article, we analyzed pedigree information on males from 12 bovine breeds born in France between 2015 and 2019. We report an overall small number of paternal lineages with, for example, a minimal number of ancestors accounting for 95% of the Y-chromosome pool of their breed ranging from only 2 to 15 individuals. Then, we mined whole-genome sequence data from 811 sires (2 ≤ n ≤ 510 per breed) and built a median-joining network using 1411 SNPs. Most branches were breed-specific and in agreement with the geographic and genetic relatedness of these populations. The within-breed haplotype diversity was lower than expected based on genealogical information, which supports the existence of major male founder effects predating pedigree recording. In addition, we observed de novo mutation events among the descendants of the same ancestors, which are of interest to define paternal sub-lineages. Our results pave the way to future studies on the estimation of the effects of Y-chromosome haplotypes on male reproductive performances and on the conservation of Y-chromosome diversity.
| S-EPMC8518513 | biostudies-literature
Project description:BACKGROUND:Apple (Malus x domestica Borkh.) is one of the most important fruit tree crops of temperate areas, with great economic and cultural value. Apple cultivars can be maintained for centuries in plant collections through grafting, and some are thought to date as far back as Roman times. Molecular markers provide a means to reconstruct pedigrees and thus shed light on the recent history of migration and trade of biological materials. The objective of the present study was to identify relationships within a set of over 1400 mostly old apple cultivars using whole-genome SNP data (~ 253 K SNPs) in order to reconstruct pedigrees. RESULTS:Using simple exclusion tests, based on counting the number of Mendelian errors, more than one thousand parent-offspring relations and 295 complete parent-offspring families were identified. Additionally, a grandparent couple was identified for the missing parental side of 26 parent-offspring pairings. Among the 407 parent-offspring relations without a second identified parent, 327 could be oriented because one of the individuals was an offspring in a complete family or by using historical data on parentage or date of recording. Parents of emblematic cultivars such as 'Ribston Pippin', 'White Transparent' and 'Braeburn' were identified. The overall pedigree combining all the identified relationships encompassed seven generations and revealed a major impact of two Renaissance cultivars of French and English origin, namely 'Reinette Franche' and 'Margil', and one North-Eastern Europe cultivar from the 1700s, 'Alexander'. On the contrary, several older cultivars, from the Middle Ages or the Roman times, had no, or only single, identifiable offspring in the set of studied accessions. Frequent crosses between cultivars originating from different European regions were identified, especially from the nineteenth century onwards. CONCLUSIONS:The availability of over 1400 apple genotypes, previously filtered for genetic uniqueness and providing a broad representation of European germplasm, has been instrumental for the success of this large pedigree reconstruction. It enlightens the history of empirical selection and recent breeding of apple cultivars in Europe and provides insights to speed-up future breeding and selection.
| S-EPMC6941274 | biostudies-literature
Project description:BACKGROUND: Advances in human genomics have allowed unprecedented productivity in terms of algorithms, software, and literature available for translating raw next-generation sequence data into high-quality information. The challenges of variant identification in organisms with lower quality reference genomes are less well documented. We explored the consequences of commonly recommended preparatory steps and the effects of single and multi sample variant identification methods using four publicly available software applications (Platypus, HaplotypeCaller, Samtools and UnifiedGenotyper) on whole genome sequence data of 65 key ancestors of Swiss dairy cattle populations. Accuracy of calling next-generation sequence variants was assessed by comparison to the same loci from medium and high-density single nucleotide variant (SNV) arrays. RESULTS: The total number of SNVs identified varied by software and method, with single (multi) sample results ranging from 17.7 to 22.0 (16.9 to 22.0) million variants. Computing time varied considerably between software. Preparatory realignment of insertions and deletions and subsequent base quality score recalibration had only minor effects on the number and quality of SNVs identified by different software, but increased computing time considerably. Average concordance for single (multi) sample results with high-density chip data was 58.3% (87.0%) and average genotype concordance in correctly identified SNVs was 99.2% (99.2%) across software. The average quality of SNVs identified, measured as the ratio of transitions to transversions, was higher using single sample methods than multi sample methods. A consensus approach using results of different software generally provided the highest variant quality in terms of transition/transversion ratio. CONCLUSIONS: Our findings serve as a reference for variant identification pipeline development in non-human organisms and help assess the implication of preparatory steps in next-generation sequencing pipelines for organisms with incomplete reference genomes (pipeline code is included). Benchmarking this information should prove particularly useful in processing next-generation sequencing data for use in genome-wide association studies and genomic selection.
| S-EPMC4289218 | biostudies-literature
Project description:Building demographic profiles in domestic dog breeds to optimize genetic trait mapping study design
2016-11-24 | GSE90441 | GEO
Project description:BackgroundAlterations in gut microbiota composition under antibiotic pressure have been widely studied, revealing a restricted diversity of gut flora, including colonization by organisms such as Enterococci, while their impact on bacterial load is variable. High-level colonization by Akkermansia muciniphila, ranging from 39% to 84% of the total bacterial population, has been recently reported in two patients being treated with broad-spectrum antibiotics, although attempts to cultivate this microorganism have been unsuccessful.ResultsHere, we propose an original approach of genome sequencing for Akkermansia muciniphila directly from the stool sample collected from one of these patients. We performed and assembly using metagenomic data obtained from the stool sample. We used a mapping method consisting of aligning metagenomic sequencing reads against the reference genome of the Akkermansia muciniphila Muc(T) strain, and a De novo assembly to support this mapping method. We obtained draft genome of the Akkermansia muciniphila strain Urmite with only 56 gaps. The absence of particular metabolic requirement as possible explanation of our inability to culture this microorganism, suggests that the bacterium was dead before the inoculation of the stool sample. Additional antibiotic resistance genes were found following comparison with the reference genome, providing some clues pertaining to its survival and colonization in the gut of a patient treated with broad-spectrum antimicrobial agents. However, no gene coding for imipenem resistance was detected, although this antibiotic was a part of the patient's antibiotic regimen.ConclusionsThis work highlights the potential of metagenomics to facilitate the assembly of genomes directly from human stool.
| S-EPMC4333879 | biostudies-literature