Comparative assessment of methods for estimating individual genome-wide homozygosity-by-descent from human genomic data

Jeanne Calment's Unique 122-Year Life Span: Facts and Factors; Longevity History in Her Genealogical Tree

Jeanne Calment's (JC) still unmatched validated human life span of 122 years and 164 days, over 3 years longer than any other, surprises many. While her case is broadly accepted as a golden standard of validation, her record age still raises skepticism among some. The probability of such a record to be achieved by someone born in the second half of the 19th century, in the world population documentarily eligible to age validation, and also in the G7 countries, can be calculated by applying some logistic and Gompertz mortality models to these populations, taken, respectively, from the age of 117 and of 100. This probability appears substantial, respectively, 7.1% and 4.7%, when using a four-parameter logistic model, which I validated on the observed survivals of centenarians until the age of 118. A 3-year interval with the second oldest is then expected. The known facts and documents constitute consistent evidence that JC died at 122: regular official records during her life, her verified memories from her 19th century life, her usage of specialized terms and of an abbreviation system specific to this period of time, photographs, her signature and handwriting, testimonies from numerous witnesses of her life, plus the expertise of gerontologists. Meanwhile, nothing contradicts her record: the daughter/mother identity swap hypothesis appears unrealistic and not supported by any evidence; especially no plausible motive can be found, on the contrary. The latest article, which defends this hypothesis, "Bayesian assessment of the longevity of JC," contains major errors, making its result subjective and invalid. The study of JC's genealogical tree on six generations, using longevity performance and total immediate ancestor longevity indicators, shows how, in two centuries, her ancestors have been living 10% longer on average at each generation, increasingly overperforming their French 25-year-old contemporaries, from around 7% in the early 18th century to 43% for her parents, and up to 56% for her older brother and 80% for herself, which suggests a progressive concentration of longevity factors. In addition to the hereditary factors, JC's personal overperformance suggests also some environmental factors, and indeed many are known. Further knowledge could be obtained by studying JC's existing blood and DNA samples: those could not only provide an additional proof of her authenticity, but more importantly could be of immense contribution for understanding deeper the factors and patterns of her longevity, and more generally the longevity and aging processes in humans in general as well.

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

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.

Inferring Individual Inbreeding and Demographic History from Segments of Identity by Descent in Ficedula Flycatcher Genome Sequences

Individual inbreeding and historical demography can be estimated by analyzing runs of homozygosity (ROH), which are indicative of chromosomal segments of identity by descent (IBD). Such analyses have so far been rare in natural populations due to limited genomic resources. We analyzed ROH in whole genome sequences from 287 Ficedula flycatchers representing four species, with the objectives of evaluating the causes of genome-wide variation in the abundance of ROH and inferring historical demography. ROH were clearly more abundant in genomic regions with low recombination rate. However, this pattern was substantially weaker when ROH were mapped using genetic rather than physical single nucleotide polymorphism (SNP) coordinates in the genome. Empirical results and simulations suggest that high ROH abundance in regions of low recombination was partly caused by increased power to detect the very long IBD segments typical of regions with a low recombination rate. Simulations also showed that hard selective sweeps (but not soft sweeps or background selection) likely contributed to variation in the abundance of ROH across the genome. Comparisons of the abundance of ROH among several study populations indicated that the Spanish pied flycatcher population had the smallest historical effective population size (N_e) for this species, and that a putatively recently founded island (Baltic) population had the smallest historical N_e among the collared flycatchers. Analysis of pairwise IBD in Baltic collared flycatchers indicated that this population was founded <60 generations ago. This study provides a rare genomic glimpse into demographic history and the mechanisms underlying the genome-wide distribution of ROH.

Runs of homozygosity: current knowledge and applications in livestock

This review presents a broader approach to the implementation and study of runs of homozygosity (ROH) in animal populations, focusing on identifying and characterizing ROH and their practical implications. ROH are continuous homozygous segments that are common in individuals and populations. The ability of these homozygous segments to give insight into a population's genetic events makes them a useful tool that can provide information about the demographic evolution of a population over time. Furthermore, ROH provide useful information about the genetic relatedness among individuals, helping to minimize the inbreeding rate and also helping to expose deleterious variants in the genome. The frequency, size and distribution of ROH in the genome are influenced by factors such as natural and artificial selection, recombination, linkage disequilibrium, population structure, mutation rate and inbreeding level. Calculating the inbreeding coefficient from molecular information from ROH (F_ROH ) is more accurate for estimating autozygosity and for detecting both past and more recent inbreeding effects than are estimates from pedigree data (F_PED ). The better results of F_ROH suggest that F_ROH can be used to infer information about the history and inbreeding levels of a population in the absence of genealogical information. The selection of superior animals has produced large phenotypic changes and has reshaped the ROH patterns in various regions of the genome. Additionally, selection increases homozygosity around the target locus, and deleterious variants are seen to occur more frequently in ROH regions. Studies involving ROH are increasingly common and provide valuable information about how the genome's architecture can disclose a population's genetic background. By revealing the molecular changes in populations over time, genome-wide information is crucial to understanding antecedent genome architecture and, therefore, to maintaining diversity and fitness in endangered livestock breeds.

Characterization of Greater Middle Eastern genetic variation for enhanced disease gene discovery

The Greater Middle East (GME) has been a central hub of human migration and population admixture. The tradition of consanguinity, variably practiced in the Persian Gulf region, North Africa, and Central Asia, has resulted in an elevated burden of recessive disease. Here we generated a whole-exome GME variome from 1,111 unrelated subjects. We detected substantial diversity and admixture in continental and subregional populations, corresponding to several ancient founder populations with little evidence of bottlenecks. Measured consanguinity rates were an order of magnitude above those in other sampled populations, and the GME population exhibited an increased burden of runs of homozygosity (ROHs) but showed no evidence for reduced burden of deleterious variation due to classically theorized 'genetic purging'. Applying this database to unsolved recessive conditions in the GME population reduced the number of potential disease-causing variants by four- to sevenfold. These results show variegated genetic architecture in GME populations and support future human genetic discoveries in Mendelian and population genetics.

Construction of relatedness matrices using genotyping-by-sequencing data

BACKGROUND

Genotyping-by-sequencing (GBS) is becoming an attractive alternative to array-based methods for genotyping individuals for a large number of single nucleotide polymorphisms (SNPs). Costs can be lowered by reducing the mean sequencing depth, but this results in genotype calls of lower quality. A common analysis strategy is to filter SNPs to just those with sufficient depth, thereby greatly reducing the number of SNPs available. We investigate methods for estimating relatedness using GBS data, including results of low depth, using theoretical calculation, simulation and application to a real data set.

RESULTS

We show that unbiased estimates of relatedness can be obtained by using only those SNPs with genotype calls in both individuals. The expected value of this estimator is independent of the SNP depth in each individual, under a model of genotype calling that includes the special case of the two alleles being read at random. In contrast, the estimator of self-relatedness does depend on the SNP depth, and we provide a modification to provide unbiased estimates of self-relatedness. We refer to these methods of estimation as kinship using GBS with depth adjustment (KGD). The estimators can be calculated using matrix methods, which allow efficient computation. Simulation results were consistent with the methods being unbiased, and suggest that the optimal sequencing depth is around 2-4 for relatedness between individuals and 5-10 for self-relatedness. Application to a real data set revealed that some SNP filtering may still be necessary, for the exclusion of SNPs which did not behave in a Mendelian fashion. A simple graphical method (a 'fin plot') is given to illustrate this issue and to guide filtering parameters.

CONCLUSION

We provide a method which gives unbiased estimates of relatedness, based on SNPs assayed by GBS, which accounts for the depth (including zero depth) of the genotype calls. This allows GBS to be applied at read depths which can be chosen to optimise the information obtained. SNPs with excess heterozygosity, often due to (partial) polyploidy or other duplications can be filtered based on a simple graphical method.

Relationship inference from the genetic data on parents or offspring: A comparative study

Relationship inference in a population is of interest for many areas of research from anthropology to genetics. It is possible to directly infer the relationship between the two individuals in a couple from their genetic data or to indirectly infer it from the genetic data of one of their offspring. For this reason, one can wonder if it is more advantageous to sample couples or single individuals to study relationships of couples in a population. Indeed, sampling two individuals is more informative than sampling one as we are looking at four haplotypes instead of two, but it also doubles the cost of the study and is a more complex sampling scheme. To answer this question, we performed simulations of 1000 trios from 10 different relationships using real human haplotypes to have realistic genome-wide genetic data. Then, we compared the genome sharing coefficients and the relationship inference obtained from either a pair of individuals or one of their offspring using both single-point and multi-point approaches. We observed that for relationships closer than 1st cousin, pairs of individuals were more informative than one of their offspring for relationship inference, and kinship coefficients obtained from single-point methods gave more accurate or equivalent genome sharing estimations. For more remote relationships, offspring were more informative for relationship inference, and inbreeding coefficients obtained from multi-point methods gave more accurate genome sharing estimations. In conclusion, relationship inference on a parental pair or on one of their offspring provides complementary information. When possible, sampling trios should be encouraged as it could allow spanning a wider range of potential relationships.

Estimation of Recent and Ancient Inbreeding in a Small Endogamous Tunisian Community Through Genomic Runs of Homozygosity

Runs of homozygosity (ROHs) are extended genomic regions of homozygous genotypes that record populations' mating patterns in the past. We performed microarray genotyping on 15 individuals from a small isolated Tunisian community. We estimated the individual and population genome-wide level of homozygosity from data on ROH above 0.5 Mb in length. We found a high average number of ROH per individual (48.2). The smallest ROH category (0.5-1.49 Mb) represents 0.93% of the whole genome, while medium-size (1.5-4.99 Mb) and long-size ROH (≥5 Mb) cover 1.18% and 0.95%, respectively. We found that genealogical individual inbreeding coefficients (Fped ) based on three- to four-generation pedigrees are not reliable indicators of the current proportion of genome-wide homozygosity inferred from ROH (FROH ) either for 0.5 or 1.5 Mb ROH length thresholds, while identity-by-descent sharing is a function of shared coancestry. This study emphasizes the effect of reproductive isolation and a prolonged practice of consanguinity that limits the genetic heterogeneity. It also provides evidence of both recent and ancient parental relatedness contribution to the current level of genome-wide homozygosity in the studied population. These findings may be useful for evaluation of long-term effects of inbreeding on human health and for future applications of ROHs in identifying recessive susceptibility genes.

Measuring individual inbreeding in the age of genomics: marker-based measures are better than pedigrees

Inbreeding (mating between relatives) can dramatically reduce the fitness of offspring by causing parts of the genome to be identical by descent. Thus, measuring individual inbreeding is crucial for ecology, evolution and conservation biology. We used computer simulations to test whether the realized proportion of the genome that is identical by descent (IBDG) is predicted better by the pedigree inbreeding coefficient (FP) or by genomic (marker-based) measures of inbreeding. Genomic estimators of IBDG included the increase in individual homozygosity relative to mean Hardy-Weinberg expected homozygosity (FH), and two measures (FROH and FE) that use mapped genetic markers to estimate IBDG. IBDG was more strongly correlated with FH, FE and FROH than with FP across a broad range of simulated scenarios when thousands of SNPs were used. For example, IBDG was more strongly correlated with FROH, FH and FE (estimated with ⩾10 000 SNPs) than with FP (estimated with 20 generations of complete pedigree) in populations with a recent reduction in the effective populations size (from Ne=500 to Ne=75). FROH, FH and FE generally explained >90% of the variance in IBDG (among individuals) when 35 K or more SNPs were used. FP explained <80% of the variation in IBDG on average in all simulated scenarios, even when pedigrees included 20 generations. Our results demonstrate that IBDG can be more precisely estimated with large numbers of genetic markers than with pedigrees. We encourage researchers to adopt genomic marker-based measures of IBDG as thousands of loci can now be genotyped in any species.

Quantifying realized inbreeding in wild and captive animal populations

Most molecular measures of inbreeding do not measure inbreeding at the scale that is most relevant for understanding inbreeding depression-namely the proportion of the genome that is identical-by-descent (IBD). The inbreeding coefficient FPed obtained from pedigrees is a valuable estimator of IBD, but pedigrees are not always available, and cannot capture inbreeding loops that reach back in time further than the pedigree. We here propose a molecular approach to quantify the realized proportion of the genome that is IBD (propIBD), and we apply this method to a wild and a captive population of zebra finches (Taeniopygia guttata). In each of 948 wild and 1057 captive individuals we analyzed available single-nucleotide polymorphism (SNP) data (260 SNPs) spread over four different genomic regions in each population. This allowed us to determine whether any of these four regions was completely homozygous within an individual, which indicates IBD with high confidence. In the highly nomadic wild population, we did not find a single case of IBD, implying that inbreeding must be extremely rare (propIBD=0-0.00094, 95% CI). In the captive population, a five-generation pedigree strongly underestimated the average amount of realized inbreeding (FPed=0.013<propIBD=0.064), as expected given that pedigree founders were already related. We suggest that this SNP-based technique is generally useful for quantifying inbreeding at the individual or population level, and we show analytically that it can capture inbreeding loops that reach back up to a few hundred generations.

Random inbreeding, isonymy, and population isolates in Argentina

Population isolates are an important tool in identifying and mapping genes of Mendelian diseases and complex traits. The geographical identification of isolates represents a priority from a genetic and health care standpoint. The purpose of this study is to analyze the spatial distribution of consanguinity by random isonymy (F ST) in Argentina and its relationship with the isolates previously identified in the country. F ST was estimated from the surname distribution of 22.6 million electors registered for the year 2001 in the 24 provinces, 5 geographical regions, and 510 departments of the country. Statistically significant spatial clustering of F ST was determined using the SaTScan V5.1 software. F ST exhibited a marked regional and departamental variation, showing the highest values towards the North and West of Argentina. The clusters of high consanguinity by random isonymy followed the same distribution. Recognized Argentinean genetic isolates are mainly localized at the north of the country, in clusters of high inbreeding. Given the availability of listings of surnames in high-capacity storage devices for different countries, estimating F ST from them can provide information on inbreeding for all levels of administrative subdivisions, to be used as a demographic variable for the identification of isolates within the country for public health purposes.

Estimates of autozygosity derived from runs of homozygosity: empirical evidence from selected cattle populations

Using genome-wide SNP data, we calculated genomic inbreeding coefficients (FROH  > 1  Mb , FROH  > 2 Mb , FROH  > 8 Mb and FROH  > 16 Mb ) derived from runs of homozygosity (ROH) of different lengths (>1, >2, >8 and > 16 Mb) as well as from levels of homozygosity (FHOM ). We compared these values of inbreeding coefficients with those calculated from pedigrees (FPED ) of 1422 bulls comprising Brown Swiss (304), Fleckvieh (502), Norwegian Red (499) and Tyrol Grey (117) cattle breeds. For all four breeds, population inbreeding levels estimated by the genomic inbreeding coefficients FROH  > 8 Mb and FROH  > 16 Mb were similar to the levels estimated from pedigrees. The lowest values were obtained for Fleckvieh (FPED  = 0.014, FROH  > 8 Mb  = 0.019 and FROH  > 16 Mb  = 0.008); the highest, for Brown Swiss (FPED  = 0.048, FROH  > 8 Mb  = 0.074 and FROH  > 16 Mb  = 0.037). In contrast, inbreeding estimates based on the genomic coefficients FROH  > 1 Mb and FROH  > 2 Mb were considerably higher than pedigree-derived estimates. Standard deviations of genomic inbreeding coefficients were, on average, 1.3-1.7-fold higher than those obtained from pedigrees. Pearson correlations between genomic and pedigree inbreeding coefficients ranged from 0.50 to 0.62 in Norwegian Red (lowest correlations) and from 0.64 to 0.72 in Tyrol Grey (highest correlations). We conclude that the proportion of the genome present in ROH provides a good indication of inbreeding levels and that analysis based on ROH length can indicate the relative amounts of autozygosity due to recent and remote ancestors.

Advances in whole-genome genetic testing: from chromosomes to microarrays

Whole-genome genetic diagnostics has changed the clinical landscape of pediatric and adolescent medicine. In this article, we review the history of clinical cytogenetics as the field has progressed from studying chromosomes prepared from cells squashed between 2 slides to the high-resolution, whole-genome technology in use today, which has allowed for the identification of numerous previously unrecognized microdeletion and microduplication syndromes. Types of arrays and the data they collect are addressed, as are the types of results that array comparative genomic hybridization studies may generate. Throughout the review, we present case stories to illustrate the familiar (Down syndrome) and the new (a never-before reported microdeletion on the long arm of chromosome 12).

Estimating the allele frequency of autosomal recessive disorders through mutational records and consanguinity: the Homozygosity Index (HI)

In principle mutational records make it possible to estimate frequencies of disease alleles (q) for autosomal recessive disorders using a novel approach based on the calculation of the Homozygosity Index (HI), i.e., the proportion of homozygous patients, which is complementary to the proportion of compound heterozygous patients P(CH). In other words, the rarer the disorder, the higher will be the HI and the lower will be the P(CH). To test this hypothesis we used mutational records of individuals affected with Familial Mediterranean Fever (FMF) and Phenylketonuria (PKU), born to either consanguineous or apparently unrelated parents from six population samples of the Mediterranean region. Despite the unavailability of precise values of the inbreeding coefficient for the general population, which are needed in the case of apparently unrelated parents, our estimates of q are very similar to those of previous descriptive epidemiological studies. Finally, we inferred from simulation studies that the minimum sample size needed to use this approach is 25 patients either with unrelated or first cousin parents. These results show that the HI can be used to produce a ranking order of allele frequencies of autosomal recessive disorders, especially in populations with high rates of consanguineous marriages.

A comparison of approaches to estimate the inbreeding coefficient and pairwise relatedness using genomic and pedigree data in a sheep population

Genome-wide SNP data provide a powerful tool to estimate pairwise relatedness among individuals and individual inbreeding coefficient. The aim of this study was to compare methods for estimating the two parameters in a Finnsheep population based on genome-wide SNPs and genealogies, separately. This study included ninety-nine Finnsheep in Finland that differed in coat colours (white, black, brown, grey, and black/white spotted) and were from a large pedigree comprising 319 119 animals. All the individuals were genotyped with the Illumina Ovine SNP50K BeadChip by the International Sheep Genomics Consortium. We identified three genetic subpopulations that corresponded approximately with the coat colours (grey, white, and black and brown) of the sheep. We detected a significant subdivision among the colour types (F(ST) = 5.4%, P<0.05). We applied robust algorithms for the genomic estimation of individual inbreeding (F(SNP)) and pairwise relatedness (Φ(SNP)) as implemented in the programs KING and PLINK, respectively. Estimates of the two parameters from pedigrees (F(PED) and Φ(PED)) were computed using the RelaX2 program. Values of the two parameters estimated from genomic and genealogical data were mostly consistent, in particular for the highly inbred animals (e.g. inbreeding coefficient F>0.0625) and pairs of closely related animals (e.g. the full- or half-sibs). Nevertheless, we also detected differences in the two parameters between the approaches, particularly with respect to the grey Finnsheep. This could be due to the smaller sample size and relative incompleteness of the pedigree for them.We conclude that the genome-wide genomic data will provide useful information on a per sample or pairwise-samples basis in cases of complex genealogies or in the absence of genealogical data.

Autozygome decoded

Consanguineous unions permit the "reunion" of ancestral chromosomal segments in a pattern referred to as "autozygosity," which is essentially a special form of homozygosity. This has long been exploited as a gene mapping tool because it is relatively easy to track a recessive mutation by the surrounding pattern of homozygous markers. The recent advent of single nucleotide polymorphism microarrays has rapidly replaced the historical use of microsatellites for this purpose. In this review, the author discusses other exciting opportunities offered by this unique arrangement of the human genome that range from pure clinical to functional genomic applications. The emerging field of whole genome sequencing promises to unlock much of the potential of the "autozygome."

A new likelihood estimator and its comparison with moment estimators of individual genome-wide diversity

The inbreeding coefficient of an individual, F, is one of the central parameters in population genetics theory. It has found important applications in evolutionary biology, conservation and ecology, such as the study of inbreeding depression. In the absence of detailed and reliable pedigree records, researchers have developed quite a few estimators to estimate F or the genome-wide homozygosity from genetic marker data. The statistical properties and comparative performances of these metrics are rarely known, however, which impedes an informed choice of the most appropriate one in practical applications. In this investigation, I propose a new likelihood F estimator that makes efficient use of marker information and takes into account of allelic dropouts, null alleles and prior knowledge of inbreeding. I compare the likelihood estimator with three moment estimators of F and three metrics of genomic homozygosity (or heterozygosity) by analysing both simulated and empirical datasets. It is shown that the likelihood estimator invariably outperforms the other estimators and metrics across all datasets analysed. For a typical dataset in heterozygosity-fitness correlation studies involving 10-20 microsatellites and 50 individuals, the correlation between the likelihood estimator and F (the simulated true inbreeding coefficient) is about 8 ∼ 35% higher than that between the moment estimators and F. A frequently applied metric, multilocus heterozygosity (MLH), and an F estimator based on the consideration of the proportion of alleles in homozygous conditions, [F R'), are shown to have particularly poor performances. The low correlation between MLH and fitness traits, which is widely observed in numerous empirical studies, might be partially caused by the adoption of this inefficient estimator of genomic inbreeding.

Does inbreeding affect N-glycosylation of human plasma proteins?

Inbreeding depression and heterosis are the two ends of phenotypic changes defined by the genome-wide homozygosity. The aim of this study was to investigate the association of genetic marker-based homozygosity estimates with 46 N-glycan features measured in human plasma. The study was based on a total of 2,341 subjects, originating from three isolated island communities in Croatia (Vis and Korcula islands) and Scotland (Orkney Islands). Inbreeding estimates were associated with an increase in tetrantennary and tetrasialylated glycans, and a decrease in digalactosylated glycans (P < 0.001). The strength of this association was proportional to the mean cohort-based inbreeding coefficient. Increase in tetraantennary glycans is known to be associated with various tumours and their association with inbreeding might be one of the mechanisms underlying the increased prevalence of tumours reported in some human isolated populations. Further studies are thus merited in order to confirm the association of inbreeding with changes in glycan profiles in other plant and animal populations, thus attempting to establish if glycosylation could indeed be involved in mediation of some phenotypic changes described in inbred and outbred organisms.

Consanguinity around the world: what do the genomic data of the HGDP-CEPH diversity panel tell us?

Inbreeding coefficients and consanguineous mating types are usually inferred from population surveys or pedigree studies. Here, we present a method to estimate them from dense genome-wide single-nucleotide polymorphism genotypes and apply it to 940 unrelated individuals from the Human Genome Diversity Panel (HGDP-CEPH). Inbreeding is observed in almost all populations of the panel, and the highest inbreeding levels and frequencies of inbred individuals are found in populations of the Middle East, Central South Asia and the Americas. In these regions, first cousin (1C) marriages are the most frequent, but we also observed marriages between double first cousins (2 × 1C) and between avuncular (AV) pairs. Interestingly, if 2 × 1C marriages are preferred to AV marriages in Central South Asia and the Middle East, the contrary is found in the Americas. There are thus some regional trends but there are also some important differences between populations within a region. Individual results can be found on the CEPH website at ftp://ftp.cephb.fr/hgdp_hbd/.

Regions of homozygosity and their impact on complex diseases and traits

Regions of homozygosity (ROHs) are more abundant in the human genome than previously thought. These regions are without heterozygosity, i.e. all the genetic variations within the regions have two identical alleles. At present there are no standardized criteria for defining the ROHs resulting in the different studies using their own criteria in the analysis of homozygosity. Compared to the era of genotyping microsatellite markers, the advent of high-density single nucleotide polymorphism genotyping arrays has provided an unparalleled opportunity to comprehensively detect these regions in the whole genome in different populations. Several studies have identified ROHs which were associated with complex phenotypes such as schizophrenia, late-onset of Alzheimer's disease and height. Collectively, these studies have conclusively shown the abundance of ROHs larger than 1 Mb in outbred populations. The homozygosity association approach holds great promise in identifying genetic susceptibility loci harboring recessive variants for complex diseases and traits.