Parentage identification using single nucleotide polymorphism genotypes: application to product tracing

Genetic diversity analysis of Inner Mongolia cashmere goats (Erlangshan subtype) based on whole genome re-sequencing

BACKGROUND

Inner Mongolia cashmere goat (IMCG), renowned for its superior cashmere quality, is a Chinese indigenous goat breed that has been developed through natural and artificial selection over a long period. However, recently, the genetic resources of IMCGs have been significantly threatened by the introduction of cosmopolitan goat breeds and the absence of adequate breed protection systems.

RESULTS

In order to assess the conservation effectiveness of IMCGs and efficiently preserve and utilize the purebred germplasm resources, this study analyzed the genetic diversity, kinship, family structure, and inbreeding of IMCGs utilizing resequencing data from 225 randomly selected individuals analyzed using the Plink (v.1.90), GCTA (v.1.94.1), and R (v.4.2.1) software. A total of 12,700,178 high-quality SNPs were selected through quality control from 34,248,064 SNP sites obtained from 225 individuals. The average minor allele frequency (MAF), polymorphic information content (PIC), and Shannon information index (SHI) were 0.253, 0.284, and 0.530, respectively. The average observed heterozygosity (Ho) and the average expected heterozygosity (He) were 0.355 and 0.351, respectively. The analysis of the identity by state distance matrix and genomic relationship matrix has shown that most individuals' genetic distance and genetic relationship are far away, and the inbreeding coefficient is low. The family structure analysis identified 10 families among the 23 rams. A total of 14,109 runs of homozygosity (ROH) were identified in the 225 individuals, with an average ROH length of 1014.547 kb. The average inbreeding coefficient, calculated from ROH, was 0.026 for the overall population and 0.027 specifically among the 23 rams, indicating a low level of inbreeding within the conserved population.

CONCLUSIONS

The IMCGs exhibited moderate polymorphism and a low level of kinship with inbreeding occurring among a limited number of individuals. Simultaneously, it is necessary to prevent the loss of bloodline to guarantee the perpetuation of the IMCGs' germplasm resources.

Assessment of kinship detection using RNA-seq data

Analysis of RNA sequencing (RNA-seq) data from related individuals is widely used in clinical and molecular genetics studies. Prediction of kinship from RNA-seq data would be useful for confirming the expected relationships in family based studies and for highlighting samples from related individuals in case-control or population based studies. Currently, reconstruction of pedigrees is largely based on SNPs or microsatellites, obtained from genotyping arrays, whole genome sequencing and whole exome sequencing. Potential problems with using RNA-seq data for kinship detection are the low proportion of the genome that it covers, the highly skewed coverage of exons of different genes depending on expression level and allele-specific expression. In this study we assess the use of RNA-seq data to detect kinship between individuals, through pairwise identity by descent (IBD) estimates. First, we obtained high quality SNPs after successive filters to minimize the effects due to allelic imbalance as well as errors in sequencing, mapping and genotyping. Then, we used these SNPs to calculate pairwise IBD estimates. By analysing both real and simulated RNA-seq data we show that it is possible to identify up to second degree relationships using RNA-seq data of even low to moderate sequencing depth.

Development of a SNP panel dedicated to parentage assignment in French sheep populations

BACKGROUND

The efficiency of breeding programs partly relies on the accuracy of the estimated breeding values which decreases when pedigrees are incomplete. Two reproduction techniques are mainly used by sheep breeders to identify the sires of lambs: animal insemination and natural matings with a single ram per group of ewes. Both methods have major drawbacks, notably time-consuming tasks for breeders, and are thus used at varying levels in breeding programs. As a consequence, the percentage of known sires can be very low in some breeds and results in less accurate estimated breeding values.

RESULTS

In order to address this issue and offer an alternative strategy for obtaining parentage information, we designed a set of 249 SNPs for parentage assignment in French sheep breeds and tested its efficiency in one breed. The set was derived from the 54 K SNP chip that was used to genotype the thirty main French sheep populations. Only SNPs in Hardy-Weinberg equilibrium, displaying the highest Minor Allele Frequency across all the thirty populations and not associated with Mendelian errors in verified family trios were selected. The panel of 249 SNPs was successfully used in an on-farm test in the BMC breed and resulted in more than 95% of lambs being assigned to a unique sire.

CONCLUSION

In this study we developed a SNP panel for assignment that achieved good results in the on-farm testing. We also raised some conditions for optimal use of this panel: at least 180 SNPs should be used and a minute preparation of the list of candidate sires. Our panel also displays high levels of MAF in the SheepHapMap breeds, particularly in the South West European breeds.

Pedigree reconstruction from SNP data: parentage assignment, sibship clustering and beyond

Data on hundreds or thousands of single nucleotide polymorphisms (SNPs) provide detailed information about the relationships between individuals, but currently few tools can turn this information into a multigenerational pedigree. I present the r package sequoia, which assigns parents, clusters half-siblings sharing an unsampled parent and assigns grandparents to half-sibships. Assignments are made after consideration of the likelihoods of all possible first-, second- and third-degree relationships between the focal individuals, as well as the traditional alternative of being unrelated. This careful exploration of the local likelihood surface is implemented in a fast, heuristic hill-climbing algorithm. Distinction between the various categories of second-degree relatives is possible when likelihoods are calculated conditional on at least one parent of each focal individual. Performance was tested on simulated data sets with realistic genotyping error rate and missingness, based on three different large pedigrees (N = 1000-2000). This included a complex pedigree with overlapping generations, occasional close inbreeding and some unknown birth years. Parentage assignment was highly accurate down to about 100 independent SNPs (error rate <0.1%) and fast (<1 min) as most pairs can be excluded from being parent-offspring based on opposite homozygosity. For full pedigree reconstruction, 40% of parents were assumed nongenotyped. Reconstruction resulted in low error rates (<0.3%), high assignment rates (>99%) in limited computation time (typically <1 h) when at least 200 independent SNPs were used. In three empirical data sets, relatedness estimated from the inferred pedigree was strongly correlated to genomic relatedness.

A high throughput single nucleotide polymorphism multiplex assay for parentage assignment in New Zealand sheep

Accurate pedigree information is critical to animal breeding systems to ensure the highest rate of genetic gain and management of inbreeding. The abundance of available genomic data, together with development of high throughput genotyping platforms, means that single nucleotide polymorphisms (SNPs) are now the DNA marker of choice for genomic selection studies. Furthermore the superior qualities of SNPs compared to microsatellite markers allows for standardization between laboratories; a property that is crucial for developing an international set of markers for traceability studies. The objective of this study was to develop a high throughput SNP assay for use in the New Zealand sheep industry that gives accurate pedigree assignment and will allow a reduction in breeder input over lambing. This required two phases of development- firstly, a method of extracting quality DNA from ear-punch tissue performed in a high throughput cost efficient manner and secondly a SNP assay that has the ability to assign paternity to progeny resulting from mob mating. A likelihood based approach to infer paternity was used where sires with the highest LOD score (log of the ratio of the likelihood given parentage to likelihood given non-parentage) are assigned. An 84 “parentage SNP panel” was developed that assigned, on average, 99% of progeny to a sire in a problem where there were 3,000 progeny from 120 mob mated sires that included numerous half sib sires. In only 6% of those cases was there another sire with at least a 0.02 probability of paternity. Furthermore dam information (either recorded, or by genotyping possible dams) was absent, highlighting the SNP test’s suitability for paternity testing. Utilization of this parentage SNP assay will allow implementation of progeny testing into large commercial farms where the improved accuracy of sire assignment and genetic evaluations will increase genetic gain in the sheep industry.

Improved estimation of inbreeding and kinship in pigs using optimized SNP panels

Background

Traditional breeding programs consider an average pairwise kinship between sibs. Based on pedigree information, the relationship matrix is used for genetic evaluations disregarding variation due to Mendelian sampling. Therefore, inbreeding and kinship coefficients are either over or underestimated resulting in reduction of accuracy of genetic evaluations and genetic progress. Single nucleotide polymorphism (SNPs) can be used to estimate pairwise kinship and individual inbreeding more accurately. The aim of this study was to optimize the selection of markers and determine the required number of SNPs for estimation of kinship and inbreeding.

Results

A total of 1,565 animals from three commercial pig populations were analyzed for 28,740 SNPs from the PorcineSNP60 Beadchip. Mean genomic inbreeding was higher than pedigree-based estimates in lines 2 and 3, but lower in line 1. As expected, a larger variation of genomic kinship estimates was observed for half and full sibs than for pedigree-based kinship reflecting Mendelian sampling. Genomic kinship between father-offspring pairs was lower (0.23) than the estimate based on pedigree (0.26). Bootstrap analyses using six reduced SNP panels (n = 500, 1000, 1500, 2000, 2500 and 3000) showed that 2,000 SNPs were able to reproduce the results very close to those obtained using the full set of unlinked markers (n = 7,984-10,235) with high correlations (inbreeding r > 0.82 and kinship r > 0.96) and low variation between different sets with the same number of SNPs.

Conclusions

Variation of kinship between sibs due to Mendelian sampling is better captured using genomic information than the pedigree-based method. Therefore, the reduced sets of SNPs could generate more accurate kinship coefficients between sibs than the pedigree-based method. Variation of genomic kinship of father-offspring pairs is recommended as a parameter to determine accuracy of the method rather than correlation with pedigree-based estimates. Inbreeding and kinship coefficients can be estimated with high accuracy using ≥2,000 unlinked SNPs within all three commercial pig lines evaluated. However, a larger number of SNPs might be necessary in other populations or across lines.

Confirmation and discovery of maternal grandsires and great-grandsires in dairy cattle

Selection, mating, and improvement of dairy animals have required accurate pedigrees. Genomic tools allow paternal ancestors to be easily confirmed or discovered because most sires are genotyped for many markers, but maternal ancestors are more difficult to discover because most female ancestors are not genotyped. Three methods to discover maternal grandsires (MGS) were developed and compared. Conflicts were counted one single nucleotide polymorphism (SNP) at a time between genotypes of the animal and potential MGS (duo method) or also using the sire's genotype (trio method). Alternatively, haplotypes of a potential MGS were matched to the animal's maternal haplotype, obtained by using linkage across loci (HAP method). The duo and trio methods can be performed as soon as a genotype is received because no imputation is required. The HAP method improved accuracy because genotypes with 2,683 (3 K) SNP were imputed to the 45,187 (50K) SNP used for genomic evaluation. The HAP method was tested using modified pedigrees with 5% of true MGS replaced by a random genotyped bull from the same birth year and 5% of MGS set to missing for 4,134 Holsteins, 552 Jerseys, and 142 Brown Swiss that had confirmed, genotyped sires. Those same animals were used to test the duo and trio methods, except that some animals had multiple genotypes and imputed dams were excluded. Accuracy measured how often the correct MGS was selected from among 12,152 genotyped Holstein, 2,265 Jersey, and 1,605 Brown Swiss potential MGS. Accuracies were 61, 60, and 65%, respectively, with the duo method; 95, 91, and 94% with the trio method; and 97, 95, and 97% with the HAP method. Accuracy of the duo method was poor (only 52% for animals genotyped with 3 K and 65% with 50K) because additional information from the paternal genotype is not used. Accuracy of the trio method was 97% with 50K but only 78% with 3K because the missing SNP were not imputed. Accuracy of the HAP method was 94% with 3 K genotypes, 98% with 50K, and 92% with nongenotyped, imputed dams. When the HAP method was extended to great-grandsires, the accuracy of maternal great-grandsire discovery was 92% for 652 Holsteins, 95% for 33 Jerseys, and 85% for 20 Brown Swiss. Accuracy was even higher using simulated genotypes. Because most dairy bulls over several generations have been genotyped, percentages of haplotypes shared with candidate males can accurately confirm, correct, or discover the sires, MGS, and even more distant ancestors of most animals.

A single nucleotide polymorphism set for paternal identification to reduce the costs of trait recording in commercial pig breeding

In animal breeding, recording of correct pedigrees is essential to achieve genetic progress. Markers on DNA are useful to verify the on-farm pedigree records (parental verification) but can also be used to assign parents retrospectively (parental identification). This approach could reduce the costs of recording for traits with low incidence, such as those related to diseases or mortality. In this study, SNP were used to assign the true sires of 368 purebred animals from a Duroc-based sire line and 140 crossbred offspring from a commercial pig population. Some of the sires were closely related. There were 3 full sibs and 17 half sibs among the true fathers and 4 full sibs and 35 half sibs among all putative fathers. To define the number of SNP necessary, 5 SNP panels (40, 60, 80, 100, and 120 SNP) were assembled from the Illumina PorcineSNP60 Beadchip (Illumina, San Diego, CA) based on minor allele frequency (>0.3), high genotyping call rate (≥90%), and equal spacing across the genome. For paternal identification considering only the 66 true sires in the data set, 60 SNP resulted in 100% correct assignment of the sire. By including additional putative sires (n = 304), 80 SNP were sufficient for 100% correct assignment of the sire. The following criteria were derived to identify the correct sire for the current data set: the logarithm of odds (LOD) score for assigning the correct sire was ≥5, the number of mismatches was ≤1, and the difference in the LOD score between the first and the second most likely sire was >5. If the correct sire was not present among all putative sires, the mean LOD for the most likely sire was close to zero or negative when using 100 SNP. More SNP would be needed for paternal identification if the number of putative sires increased and the degree of relatedness was greater than in the data set used here. The threshold for the number of mismatches can be adjusted according to the practical situation to account for the trade-off between false negatives and false positives. The latter can be avoided efficiently, ensuring that the correct father is being sampled. Nevertheless, a restriction on the number of putative sires is advisable to reduce the risk of assigning close relatives.

Parentage and sibship inference from multilocus genotype data under polygamy

Likelihood methods have been developed to partition individuals in a sample into sibling clusters using genetic marker data without parental information. Most of these methods assume either both sexes are monogamous to infer full sibships only or only one sex is polygamous to infer full sibships and paternal or maternal (but not both) half sibships. We extend our previous method to the more general case of both sexes being polygamous to infer full sibships, paternal half sibships, and maternal half sibships and to the case of a two-generation sample of individuals to infer parentage jointly with sibships. The extension not only expands enormously the scope of application of the method, but also increases its statistical power. The method is implemented for both diploid and haplodiploid species and for codominant and dominant markers, with mutations and genotyping errors accommodated. The performance and robustness of the method are evaluated by analyzing both simulated and empirical data sets. Our method is shown to be much more powerful than pairwise methods in both parentage and sibship assignments because of the more efficient use of marker information. It is little affected by inbreeding in parents and is moderately robust to nonrandom mating and linkage of markers. We also show that individually much less informative markers, such as SNPs or AFLPs, can reach the same power for parentage and sibship inferences as the highly informative marker simple sequence repeats (SSRs), as long as a sufficient number of loci are employed in the analysis.