Effect of reduced genomic representation on using runs of homozygosity for inbreeding characterization

Genomic measures of inbreeding based on identical-by-descent (IBD) segments are increasingly used to measure inbreeding and mostly estimated on SNP arrays and whole-genome sequencing (WGS) data. However, some softwares recurrently used for their estimation assume that genomic positions which have not been genotyped are nonvariant. This might be true for WGS data, but not for reduced genomic representations and can lead to spurious IBD segments estimation. In this project, we simulated the outputs of WGS, two SNP arrays of different sizes and RAD-sequencing for three populations with different sizes and histories. We compare the results of IBD segments estimation with two softwares: runs of homozygosity (ROHs) estimated with PLINK and homozygous-by-descent (HBD) segments estimated with RZooRoH. We demonstrate that to obtain meaningful estimates of inbreeding, RZooRoH requires a SNPs density 11 times smaller compared to PLINK: ranks of inbreeding coefficients were conserved among individuals above 22 SNPs/Mb for PLINK and 2 SNPs/Mb for RZooRoH. We also show that in populations with simple demographic histories, distribution of ROHs and HBD segments are correctly estimated with both SNP arrays and WGS. PLINK correctly estimated distribution of ROHs with SNP densities above 22 SNPs/Mb, while RZooRoH correctly estimated distribution of HBD segments with SNPs densities above 11 SNPs/Mb. However, in a population with a more complex demographic history, RZooRoH resulted in better distribution of IBD segments estimation compared to PLINK even with WGS data. Consequently, we advise researchers to use either methods relying on excess homozygosity averaged across SNPs or model-based HBD segments calling methods for inbreeding estimations.     

Genomic inbreeding estimation in small populations: evaluation of runs of homozygosity in three local dairy cattle breeds

In the local breeds with small population size, one of the most important problems is the increase of inbreeding coefficient (F). High levels of inbreeding lead to reduced genetic diversity and inbreeding depression. The availability of high-density single nucleotide polymorphism (SNP) arrays has facilitated the quantification of F by genomic markers in farm animals. Runs of homozygosity (ROH) are contiguous lengths of homozygous genotypes and represent an estimate of the degree of autozygosity at genome-wide level. The current study aims to quantify the genomic F derived from ROH (F_ROH) in three local dairy cattle breeds. F_ROH values were compared with F estimated from the genomic relationship matrix (F_GRM), based on the difference between observed v. expected number of homozygous genotypes (F_HOM) and the genomic homozygosity of individual i (F_{MOL i}). The molecular coancestry coefficient (f_{MOL ij}) between individuals i and j was also estimated. Individuals of Cinisara (71), Modicana (72) and Reggiana (168) were genotyped with the 50K v2 Illumina BeadChip. Genotypes from 96 animals of Italian Holstein cattle breed were also included in the analysis. We used a definition of ROH as tracts of homozygous genotypes that were >4 Mb. Among breeds, 3661 ROH were identified. Modicana showed the highest mean number of ROH per individual and the highest value of F_ROH, whereas Reggiana showed the lowest ones. Differences among breeds existed for the ROH lengths. The individuals of Italian Holstein showed high number of short ROH segments, related to ancient consanguinity. Similar results showed the Reggiana with some extreme animals with segments covering 400 Mb and more of genome. Modicana and Cinisara showed similar results between them with the total length of ROH characterized by the presence of large segments. High correlation was found between F_HOM and F_ROH ranged from 0.83 in Reggiana to 0.95 in Cinisara and Modicana. The correlations among F_ROH and other estimated F coefficients were generally lower ranged from 0.45 (F_{MOL i}−F_ROH) in Cinisara to 0.17 (F_GRM−F_ROH) in Modicana. On the basis of our results, recent inbreeding was observed in local breeds, considering that 16 Mb segments are expected to present inbreeding up to three generations ago. Our results showed the necessity of implementing conservation programs to control the rise of inbreeding and coancestry in the three Italian local dairy cattle breeds.     

Analysis of runs of homozygosity and their relationship with inbreeding in five cattle breeds farmed in Italy

Increased inbreeding is an inevitable consequence of selection in livestock populations. The analysis of high‐density single nucleotide polymorphisms (SNPs) facilitates the identification of long and uninterrupted runs of homozygosity (ROH) that can be used to identify chromosomal regions that are identical by descent. In this work, the distribution of ROH of different lengths in five Italian cattle breeds is described. A total of 4095 bulls from five cattle breeds (2093 Italian Holstein, 749 Italian Brown, 364 Piedmontese, 410 Marchigiana and 479 Italian Simmental) were genotyped at 54K SNP loci. ROH were identified and used to estimate molecular inbreeding coefficients (F_ROH), which were compared with inbreeding coefficients estimated from pedigree information (F_PED) and using the genomic relationship matrix (F_GRM). The average number of ROH per animal ranged from 54 ± 7.2 in Piedmontese to 94.6 ± 11.6 in Italian Brown. The highest number of short ROH (related to ancient consanguinity) was found in Piedmontese, followed by Simmental. The Italian Brown and Holstein had a higher proportion of longer ROH distributed across the whole genome, revealing recent inbreeding. The F_PED were moderately correlated with F_ROH > 1 Mb (0.662, 0.700 and 0.669 in Italian Brown, Italian Holstein and Italian Simmental respectively) but poorly correlated with F_GRM (0.134, 0.128 and 0.448 for Italian Brown, Italian Holstein and Italian Simmental respectively). The inclusion of ROH > 8 Mb in the inbreeding calculation improved the correlation of F_ROH with F_PED and F_GRM. ROH are a direct measure of autozygosity at the DNA level and can overcome approximations and errors resulting from incomplete pedigree data. In populations with high linkage disequilibrium (LD) and recent inbreeding (e.g. Italian Holstein and Italian Brown), a medium‐density marker panel, such as the one used here, may provide a good estimate of inbreeding. However, in populations with low LD and ancient inbreeding, marker density would have to be increased to identify short ROH that are identical by descent more precisely.     

Increased inbreeding but not homozygosity in small populations of Sabatia angularis (Gentianaceae)

Understanding how the mating system varies with population size in plant populations is critical for understanding their genetic and demographic fates. We examined how the mating system, characterized by outcrossing rate, biparental inbreeding rate, and inbreeding coefficient, and genetic diversity varied with population size in natural populations of the biennial Sabatia angularis. We found a significant, positive relationship between outcrossing and population size. Selfing was as high as 40% in one small population but was only 7% in the largest population. Despite this pattern, observed heterozygosity did not vary with population size, and we suggest that selection against inbred individuals maintains observed heterozygosity in small populations. Consistent with this hypothesis, we found a trend of lower inbreeding coefficients in the maternal than progeny generation in all of the populations, and half of the populations exhibited significant excesses of adult heterozygosity. Moreover, genetic diversity was not related to population size and was similar across all populations examined. Our results suggest that the consequences of increased selfing for population fitness in S. angularis, a species that experiences significant inbreeding depression, will depend on the relative magnitude and consistency of inbreeding depression and the demographic cost of selection for outcrossed progeny in small populations.     

Genomic prediction based on runs of homozygosity

Background

Genomic prediction is based on the accurate estimation of the genomic relationships among and between training animals and selection candidates in order to obtain accurate estimates of the genomic estimated breeding values (GEBV). Various methods have been used to predict GEBV based on population-wide linkage disequilibrium relationships (G_IBS) or sometimes on linkage analysis relationships (G_LA). Here, we propose a novel method to predict GEBV based on a genomic relationship matrix using runs of homozygosity (G_ROH). Runs of homozygosity were used to derive probabilities of multi-locus identity by descent chromosome segments. The accuracy and bias of the prediction of GEBV using G_ROH were compared to those using G_IBS and G_LA. Comparisons were performed using simulated datasets derived from a random pedigree and a real pedigree of Italian Brown Swiss bulls. The comparison of accuracies of GEBV was also performed on data from 1086 Italian Brown Swiss dairy cattle.

Results

Simulations with various thresholds of minor allele frequency for markers and quantitative trait loci showed that G_ROH achieved consistently more accurate GEBV (0 to 4% points higher) than G_IBS and G_LA. The bias of GEBV prediction for simulated data was higher based on the real pedigree than based on a random pedigree. In the analyses with real data, G_ROH and G_LA had similar accuracies. However, G_LA achieved a higher accuracy when the prediction was done on the youngest animals. The G_IBS matrices calculated with and without standardized marker genotypes resulted in similar accuracies.

Conclusions

The present study proposes G_ROH as a novel method to estimate genomic relationship matrices and predict GEBV based on runs of homozygosity and shows that it can result in higher or similar accuracies of GEBV prediction than G_LA, except for the real data analysis with validation of young animals. Compared to G_IBS, G_ROH resulted in more accurate GEBV predictions.     

Use of runs statistics for pattern recognition in genomic DNA sequences.

In this article, the use of the finite Markov chain imbedding (FMCI) technique to study patterns in DNA under a hidden Markov model (HMM) is introduced. With a vision of studying multiple runs-related statistics simultaneously under an HMM through the FMCI technique, this work establishes an investigation of a bivariate runs statistic under a binary HMM for DNA pattern recognition. An FMCI-based recursive algorithm is derived and implemented for the determination of the exact distribution of this bivariate runs statistic under an independent identically distributed (IID) framework, a Markov chain (MC) framework, and a binary HMM framework. With this algorithm, we have studied the distributions of the bivariate runs statistic under different binary HMM parameter sets; probabilistic profiles of runs are created and shown to be useful for trapping HMM maximum likelihood estimates (MLEs). This MLE-trapping scheme offers good initial estimates to jump-start the expectation-maximization (EM) algorithm in HMM parameter estimation and helps prevent the EM estimates from landing on a local maximum or a saddle point. Applications of the bivariate runs statistic and the probabilistic profiles in conjunction with binary HMMs for pattern recognition in genomic DNA sequences are illustrated via case studies on DNA bendability signals using human DNA data.     

Genomic runs of homozygosity record population history and consanguinity

The human genome is characterised by many runs of homozygous genotypes, where identical haplotypes were inherited from each parent. The length of each run is determined partly by the number of generations since the common ancestor: offspring of cousin marriages have long runs of homozygosity (ROH), while the numerous shorter tracts relate to shared ancestry tens and hundreds of generations ago. Human populations have experienced a wide range of demographic histories and hold diverse cultural attitudes to consanguinity. In a global population dataset, genome-wide analysis of long and shorter ROH allows categorisation of the mainly indigenous populations sampled here into four major groups in which the majority of the population are inferred to have: (a) recent parental relatedness (south and west Asians); (b) shared parental ancestry arising hundreds to thousands of years ago through long term isolation and restricted effective population size (N(e)), but little recent inbreeding (Oceanians); (c) both ancient and recent parental relatedness (Native Americans); and (d) only the background level of shared ancestry relating to continental N(e) (predominantly urban Europeans and East Asians; lowest of all in sub-Saharan African agriculturalists), and the occasional cryptically inbred individual. Moreover, individuals can be positioned along axes representing this demographic historic space. Long runs of homozygosity are therefore a globally widespread and under-appreciated characteristic of our genomes, which record past consanguinity and population isolation and provide a distinctive record of the demographic history of an individual's ancestors. Individual ROH measures will also allow quantification of the disease risk arising from polygenic recessive effects.     

Using genomic inbreeding coefficient estimates for homozygosity mapping of rare recessive traits: application to Taybi-Linder syndrome

The use of inbred patients whose exact genealogy may not be available is of primary interest in mapping genes involved in rare recessive diseases. We show here that this can be achieved by estimating inbreeding coefficients from the patients' genomic information and using these estimates to perform homozygosity mapping. We show the interest of the approach by mapping a gene for Taybi-Linder syndrome to chromosome 2q, with the use of a key patient with no genealogical information.     

Coefficients of inbreeding and homozygosity in recurrent selection: The case of m linked loci

Summary Methods of calculating the coefficients of inbreeding and homozygosity in a finite population undergoing recurrent selection (self-select-intercross in succeeding generations) are investigated for the case of m linked loci and effective directional selection. These coefficients are derived in terms of vectors whose components reflect the various possible patterns of genes being identical at a given stage of the recurrent selection breeding program.For the case of two linked loci the progress of the panmictic index and/or the index of total heterozygosity through twenty-five cycles of recurrent selection is traced by means of computer-simulated populations ranging in sizes from ten through one hundred, assuming varying recombination probabilities, and assuming both minimum and maximum inbreeding selection patterns.Results indicate that the coefficient of relationship in the source population is extremely important in tracing the progress of the degree of inbreeding and/or total homozygosity, that linkage plays a major role in promoting heterozygosity in a recurrent selection system, and that careful intercrossing rather than random mating in alternate generations of the recurrent selection cycle is important in promoting maximum heterozygosity in the selected population. In the simulated populations the effect of small population sizes is observed and, in general, indications are that unless more than five complete recurrent cycles are contemplated, increasing the population size results in only relatively minor increases in panmixia, especially when linked loci are involved in the selected trait and when care is taken to avoid a maximum inbreeding selection pattern.     

Coefficients of inbreeding and homozygosity in recurrent selection: the one-locus case

Summary For selection programs which can be represented by successive self-select-intercross cycles (such as recurrent selection or reciprocal recurrent selection) general recurrence formulae are developed for obtaining the coefficients of inbreeding and homozygosity in each cycle. The formula for the coefficient of inbreeding is a generalization of a result given by Sprague, et al. (1952). It is shown that the coefficient of parentage in the source population has a major effect on the coefficient of inbreeding in the following cycles as does the population size. The relationship of both types of coefficients and their importance in practical work are discussed.

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Zusammenfassung Für Selektionsprogramme, die durch aufeinanderfolgende Selbstungs-Selektions-Kreuzungs-Zyklen (wie z. B. rekurrente Selektion oder reziproke rekurrente Selektion) charakterisiert sind, werden allgemeine Rekurrenzformeln zur Berechnung von Inzucht- und Homozygotie-Koeffizienten in jedem Zyklus entwickelt.Die Formel für den Inzuchtkoeffizienten stellt eine Verallgemeinerung eines von Sprague et al. (1952) erhaltenen Ergebnisses dar.Es wird gezeigt, daß der coefficient of parentage der Ausgangspopulation ebenso wie die Populations größe einen nachhaltigen Einfluß auf den Inzucht-koeffizienten der folgenden Zyklen haben. Die Beziehung beider Typen von Koeffizienten und ihre Bedeutung für die praktische Arbeit werden diskutiert.

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Now at Morehead State University.     

A genome-wide homozygosity association study identifies runs of homozygosity associated with rheumatoid arthritis in the human major histocompatibility complex

Rheumatoid arthritis (RA) is a chronic inflammatory disorder with a polygenic mode of inheritance. This study examined the hypothesis that runs of homozygosity (ROHs) play a recessive-acting role in the underlying RA genetic mechanism and identified RA-associated ROHs. Ours is the first genome-wide homozygosity association study for RA and characterized the ROH patterns associated with RA in the genomes of 2,000 RA patients and 3,000 normal controls of the Wellcome Trust Case Control Consortium. Genome scans consistently pinpointed two regions within the human major histocompatibility complex region containing RA-associated ROHs. The first region is from 32,451,664 bp to 32,846,093 bp (-log10(p)>22.6591). RA-susceptibility genes, such as HLA-DRB1, are contained in this region. The second region ranges from 32,933,485 bp to 33,585,118 bp (-log10(p)>8.3644) and contains other HLA-DPA1 and HLA-DPB1 genes. These two regions are physically close but are located in different blocks of linkage disequilibrium, and ～40% of the RA patients' genomes carry these ROHs in the two regions. By analyzing homozygote intensities, an ROH that is anchored by the single nucleotide polymorphism rs2027852 and flanked by HLA-DRB6 and HLA-DRB1 was found associated with increased risk for RA. The presence of this risky ROH provides a 62% accuracy to predict RA disease status. An independent genomic dataset from 868 RA patients and 1,194 control subjects of the North American Rheumatoid Arthritis Consortium successfully validated the results obtained using the Wellcome Trust Case Control Consortium data. In conclusion, this genome-wide homozygosity association study provides an alternative to allelic association mapping for the identification of recessive variants responsible for RA. The identified RA-associated ROHs uncover recessive components and missing heritability associated with RA and other autoimmune diseases.     

Amino acids runs and genomic compositional biases in vertebrates

A compositional analysis of a sample of 50 zebrafish proteins containing at least one alanine run and of their open reading frames (ORFs) has been performed. The sample of poly(Ala) proteins showed a tendency to have runs of other amino acids (His/H, Gln/Q, Ser/S, Pro/P). Their ORFs and the first and second codon positions had higher GC contents than a reference gene set. The "universal" correlation between the GC content of the first+second and third codon positions (GC1+2 vs GC3) does not hold, but I provide an explanation in terms of genomic heterogeneity. Significant correlation between AHQS content and GC3 was obtained, reflecting codon bias favoring G/C at the third codon position of these amino acids. A correspondence analysis (COA) of relative synonymous codon usage showed that the poly(Ala) proteins have a biased distribution according to the second axis of the COA, which correlates with gene expression in zebrafish. A comparison with human is undertaken.     

Relationship of runs of homozygosity with adaptive and production traits in a paternal broiler line

Genomic regions under high selective pressure present specific runs of homozygosity (ROH), which provide valuable information on the genetic mechanisms underlying the adaptation to environment imposed challenges. In broiler chickens, the adaptation to conventional production systems in tropical environments lead the animals with favorable genotypes to be naturally selected, increasing the frequency of these alleles in the next generations. In this study, ~1400 chickens from a paternal broiler line were genotyped with the 600 K Affymetrix® Axiom® high-density (HD) genotyping array for estimation of linkage disequilibrium (LD), effective population size (N_e), inbreeding and ROH. The average LD between adjacent single nucleotide polymorphisms (SNPs) in all autosomes was 0.37, and the LD decay was higher in microchromosomes followed by intermediate and macrochromosomes. The N_e of the ancestral population was high and declined over time maintaining a sufficient number of animals to keep the inbreeding coefficient of this population at low levels. The ROH analysis revealed genomic regions that harbor genes associated with homeostasis maintenance and immune system mechanisms, which may have been selected in response to heat stress. Our results give a comprehensive insight into the relationship between shared ROH regions and putative regions related to survival and production traits in a paternal broiler line selected for over 20 years. These findings contribute to the understanding of the effects of environmental and artificial selection in shaping the distribution of functional variants in the chicken genome.     

Genomic patterns of homozygosity in worldwide human populations

Genome-wide patterns of homozygosity runs and their variation across individuals provide a valuable and often untapped resource for studying human genetic diversity and evolutionary history. Using genotype data at 577,489 autosomal SNPs, we employed a likelihood-based approach to identify runs of homozygosity (ROH) in 1,839 individuals representing 64 worldwide populations, classifying them by length into three classes—short, intermediate, and long—with a model-based clustering algorithm. For each class, the number and total length of ROH per individual show considerable variation across individuals and populations. The total lengths of short and intermediate ROH per individual increase with the distance of a population from East Africa, in agreement with similar patterns previously observed for locus-wise homozygosity and linkage disequilibrium. By contrast, total lengths of long ROH show large interindividual variations that probably reflect recent inbreeding patterns, with higher values occurring more often in populations with known high frequencies of consanguineous unions. Across the genome, distributions of ROH are not uniform, and they have distinctive continental patterns. ROH frequencies across the genome are correlated with local genomic variables such as recombination rate, as well as with signals of recent positive selection. In addition, long ROH are more frequent in genomic regions harboring genes associated with autosomal-dominant diseases than in regions not implicated in Mendelian diseases. These results provide insight into the way in which homozygosity patterns are produced, and they generate baseline homozygosity patterns that can be used to aid homozygosity mapping of genes associated with recessive diseases.     

Genome-wide identification of runs of homozygosity islands and associated genes in local dairy cattle breeds

Runs of homozygosity (ROH) are widely used as predictors of whole-genome inbreeding levels in cattle. They identify regions that have an unfavorable effect on a phenotype when homozygous, but also identify the genes associated with traits of economic interest present in these regions. Here, the distribution of ROH islands and enriched genes within these regions in four dairy cattle breeds were investigated. Cinisara (71), Modicana (72), Reggiana (168) and Italian Holstein (96) individuals were genotyped using the 50K v2 Illumina BeadChip. The genomic regions most commonly associated with ROHs were identified by selecting the top 1% of the single nucleotide polymorphisms (SNPs) most commonly observed in the ROH of each breed. In total, 11 genomic regions were identified in Cinisara and Italian Holstein, and eight in Modicana and Reggiana, indicating an increased ROH frequency level. Generally, ROH islands differed between breeds. The most homozygous region (>45% of individuals with ROH) was found in Modicana on chromosome 6 within a quantitative trail locus affecting milk fat and protein concentrations. We identified between 126 and 347 genes within ROH islands, which are involved in multiple signaling and signal transduction pathways in a wide variety of biological processes. The gene ontology enrichment provided information on possible molecular functions, biological processes and cellular components under selection related to milk production, reproduction, immune response and resistance/susceptibility to infection and diseases. Thus, scanning the genome for ROH could be an alternative strategy to detect genomic regions and genes related to important economic traits.