Pairwise Kinship Research Articles

Evaluating the effects of silent genes on pairwise kinship testing

Short tandem repeat (STR) loci are frequently utilized in kinship testing, and mutations of a single base occurring in the primer-binding region of the STR locus can result in the failure of allelic amplification and the emergence of silent genes. Silent genes are not observable and, therefore, are excluded from the genotypes assessed. Pedigree likelihood ratios (LRs) are often employed in kinship testing to determine the likelihood of different kinship scenarios. LR values are derived from various types of genotypes. LRexact values are based on the exact or actual genotypes, which may include silent genes. Conversely, LRobserve values are based on observed genotypes that exclude silent genes, while LRadjust values incorporate all potential genotypes, including both observed and those with silent genes. Initially, the formulae for LRs in 1st degree, 2nd degree, and 3rd degree kinship testing are presented according to different genotype forms of pairwise individuals. The correctness of these formulae is then verified using the Familias software, and the results are compared with those from the GeneVisa software (www.genevisa.net). Lastly, the simulation modules of GeneVisa are used to assess the impact of silent genes on pairwise kinship testing. The findings indicate that the overall impact of silent genes is minimal, although in some cases, the effects can be relatively significant. The influence of silent genes generally decreases as the kinship relationship becomes more distant. In specific kinship tests, the effect of silent genes is reduced when the individuals are unrelated compared to when there is a kinship relationship. Utilizing the LRadjust value for 1st degree and 2nd degree kinship testing can substantially mitigate the effects of silent genes.

Local versus regional patterns in zoospore dispersal of the kelp Eisenia bicyclis (Laminariales, Phaeophyceae)

SummaryIt is generally accepted that kelp populations have a metapopulation structure. Most zoospores settle near to their parent individual, and infrequent but long‐distance dispersal of zoospores contributes to gene flow between local populations. Population genetic analysis of single nucleotide polymorphism genotyping by MIG‐seq (i.e. multiplexed inter‐simple sequence repeats genotyping by sequencing) was performed on the dominant kelp, Eisenia bicyclis, in two areas: Kitsunezaki (a sheltered area) and Shimoda (an exposed site). Regional scale analysis of genetic structure was conducted at six sites in Kitsunezaki and three sites in Shimoda. When viewed on a regional scale based on the inbreeding coefficient within the local population, the inbreeding ratio was higher in Shimoda than in Kitsunezaki, probably as a result of the limited vertical zonal distribution in the exposed environment. Vertically wide distribution in the sheltered environment apparently enabled frequent crossing among individuals in Kitsunezaki. By contrast, when viewed on a local scale based on the pairwise kinship coefficient (FST) between populations, gene flow among local populations in Shimoda occurred over a wide area, but was limited in Kitsunezaki. In Shimoda, genetic exchange between local populations, even if inbreeding is locally active, is likely to support metapopulation maintenance and rapid recovery of local populations. In Kitsunezaki, however, genetic exchange among local populations is limited within few 100 m, and the metapopulation structure will decline in the long term because of inbreeding depression. Local dispersal distance of zoospores was investigated based on parent–offspring analysis in the Kitsunezaki population, which revealed that zoospores mainly settled within 5 m of their parent. However, some zoospores traveled over 27 m within the 4 × 30 m study area. The present study shows the importance of examination at different spatial scales when investigating zoospore dispersal of laminarialean kelps.

Performance of a 74-Microhaplotype Assay in Kinship Analyses.

Microhaplotypes (MHs) consisting of multiple SNPs and indels on short stretches of DNA are new and interesting loci for forensic genetic investigations. In this study, we analysed 74 previously defined MHs in two of the populations that our laboratory provides with forensic genetic services, Danes and Greenlanders. In addition to the 229 SNPs that originally made up the 74 MHs, 66 SNPs and 3 indels were identified in the two populations, and 45 of these variants were included in new definitions of the MHs, whereas 24 SNPs were considered rare and of little value for case work. The average effective number of alleles (Ae) was 3.2, 3.0, and 2.6 in Danes, West Greenlanders, and East Greenlanders, respectively. High levels of linkage disequilibrium were observed in East Greenlanders, which reflects the characteristics of this population that has a small size, and signs of admixture and substructure. Pairwise kinship simulations of full siblings, half-siblings, first cousins, and unrelated individuals were performed using allele frequencies from MHs, STRs and SNPs from Danish and Greenlandic populations. The MH panel outperformed the currently used STR and SNP marker sets and was able to differentiate siblings from unrelated individuals with a 0% false positive rate and a 1.1% false negative rate using an LR threshold of 10,000 in the Danish population. However, the panel was not able to differentiate half-siblings or first cousins from unrelated individuals. The results generated in this study will be used to implement MHs as investigative markers for relationship testing in our laboratory.

An approach to unified formulae for likelihood ratio calculation in pairwise kinship analysis.

Introduction: The likelihood ratio (LR) can be an efficient means of distinguishing various relationships in forensic fields. However, traditional list-based methods for derivation and presentation of LRs in distant or complex relationships hinder code editing and software programming. This paper proposes an approach for a unified formula for LRs, in which differences in participants' genotype combinations can be ignored for specific identification. This formula could reduce the difficulty of by-hand coding, as well as running time of large-sample-size simulation. Methods: The approach is first applied to a problem of kinship identification in which at least one of the participants is alleged to be inbred. This can be divided into two parts: i) the probability of different identical by descent (IBD) states according to the alleged kinship; and ii) the ratio of the probability that specific genotype combination can be detected assuming the alleged kinship exists between the two participants to the similar probability assuming that they are unrelated, for each state. For the probability, there are usually recognized results for common identification purposes. For the ratio, subscript letters representing IBD alleles of individual A's alleles are used to eliminate differences in genotype combinations between the two individuals and to obtain a unified formula for the ratio in each state. The unification is further simplified for identification cases in which it is alleged that both of the participants are outbred. Verification is performed to show that the results obtained with the unified and list-form formulae are equivalent. Results: A series of unified formulae are derived for different identification purposes, based on which an R package named KINSIMU has been developed and evaluated for use in large-size simulations for kinship analysis. Comparison between the package with two existing tools indicated that the unified approach presented here is more convenient and time-saving with respect to the coding process for computer applications compared with the list-based approach, despite appearing more complicated. Moreover, the method of derivation could be extended to other identification problems, such as those with different hypothesis sets or those involving multiple individuals. Conclusion: The unified approach of LR calculation can be beneficial in kinship identification field.

Estimation of inbreeding and kinship coefficients via latent identity-by-descent states.

Estimating the individual inbreeding coefficient and pairwise kinship is an important problem in human genetics (e.g. in disease mapping) and in animal and plant genetics (e.g. inbreeding design). Existing methods, such as sample correlation-based genetic relationship matrix, KING, and UKin, are either biased, or not able to estimate inbreeding coefficients, or produce a large proportion of negative estimates that are difficult to interpret. This limitation of existing methods is partly due to failure to explicitly model inbreeding. Since all humans are inbred to various degrees by virtue of shared ancestries, it is prudent to account for inbreeding when inferring kinship between individuals. We present "Kindred," an approach that estimates inbreeding and kinship by modeling latent identity-by-descent states that accounts for all possible allele sharing-including inbreeding-between two individuals. Kindred used non-negative least squares method to fit the model, which not only increases computation efficiency compared to the maximum likelihood method, but also guarantees non-negativity of the kinship estimates. Through simulation, we demonstrate the high accuracy and non-negativity of kinship estimates by Kindred. By selecting a subset of SNPs that are similar in allele frequencies across different continental populations, Kindred can accurately estimate kinship between admixed samples. In addition, we demonstrate that the realized kinship matrix estimated by Kindred is effective in reducing genomic control values via linear mixed model in genome-wide association studies. Finally, we demonstrate that Kindred produces sensible heritability estimates on an Australian height dataset. Kindred is implemented in C with multi-threading. It takes vcf file or stream as input and works seamlessly with bcftools. Kindred is freely available at https://github.com/haplotype/kindred.

DArTseq-based SNP markers reveal high genetic diversity among early generation fall armyworm tolerant maize inbred lines.

Diversity analysis using molecular markers serves as a powerful tool in unravelling the intricacies of inclusivity within various populations and is an initial step in the assessment of populations and the development of inbred lines for host plant resistance in maize. This study was conducted to assess the genetic diversity and population structure of 242 newly developed S3 inbred lines using 3,305 single nucleotide polymorphism (SNP) markers and to also assess the level of homozygosity achieved in each of the inbred lines. A total of 1,184 SNP markers were found highly informative, with a mean polymorphic information content (PIC) of 0.23. Gene diversity was high among the inbred lines, ranging from 0.04 to 0.50, with an average of 0.27. The residual heterozygosity of the 242 S3 inbred lines averaged 8.8%, indicating moderately low heterozygosity levels among the inbred lines. Eighty-four percent of the 58,322 pairwise kinship coefficients among the inbred lines were near zero (0.00-0.05), with only 0.3% of them above 0.50. These results revealed that many of the inbred lines were distantly related, but none were redundant, suggesting each inbred line had a unique genetic makeup with great potential to provide novel alleles for maize improvement. The admixture-based structure analysis, principal coordinate analysis, and neighbour-joining clustering were concordant in dividing the 242 inbred lines into three subgroups based on the pedigree and selection history of the inbred lines. These findings could guide the effective use of the newly developed inbred lines and their evaluation in quantitative genetics and molecular studies to identify candidate lines for breeding locally adapted fall armyworm tolerant varieties in Ghana and other countries in West and Central Africa.

Applications of 1993 single nucleotide polymorphism loci in forensic pairwise kinship identifications and inferences

Kinship testing plays critical roles in criminal investigations, missing person searches, civil disputes, as well as identifying disaster victims. The existing commonly used short tandem repeat (STR) loci have limited effectiveness in the identification of second-degree and more distant kinships. In this study, a total of 1993 SNP loci of 119 Chinese Han individuals from eight families were sequenced on the MGISEQ-2000RS platform. The system powers of this panel for kinship identifications were evaluated based on both the likelihood ratio (LR) and identical by state (IBS) methods. The results indicated that this panel could be used as an effective tool to kinship analyses including paternity testing, full sibling testing, second-degree kinships, and first cousin kinship analyses. Both the LR and IBS methods could be applied in distinguishing first-degree and second-degree pairs from unrelated individuals. Based on the 1993 SNP loci, LR>1000 and LR<0.001 are recommended as the thresholds of identifying first-cousin kinships from unrelated individuals, and the system power of such thresholds was 0.9470. Besides, kinship coefficients for different kinship pairs were estimated and then were used to predict the kinships for pairwise individuals. This panel performs an effective kinship inference power for the predictions of first-degree, second-degree kinships and unrelated individual pairs, while presenting low sensitivity in the prediction of first-cousin kinships.

Reproductive characteristics, population genetics, and pairwise kinship inform strategic recovery of a plant species in a fragmented landscape

AbstractPopulation genetics and understanding of mating systems provide fundamental information for conservation planning. Pairing these methods is a powerful tool in the study of threatened species, however, they are rarely applied in concert. We examined the mating system and used molecular genetics to measure pairwise kinship and the potential for inbreeding inHibbertia spanantha, a critically endangered long‐lived shrub endemic to the Sydney Basin, Australia, as a model for conservation planning of species in highly fragmented populations. In situ hand pollination experiments demonstrated that the species is preferentially outcrossing, with limited ability to self‐pollinate (either autogamously or geitonogamously). Although population genetics confirmed high levels of kinship and clonality, there is currently enough population heterozygosity for successful open pollination, primarily through buzz pollination by Sweat Bees (Lasioglossum [Chilalictus]). High levels of clonality and population kinship in one population may be the cause of reduced fitness, identified because our outcrossing pollination treatment produced significantly more seeds with greater viability and seed mass than the open treatments. Differences in weight of filled (viable) seeds were identified between populations, although not treatments, where clonal dominance may be swamping pollinator foraging activities. Identification of species mating system, population reproductive capacity, and impacts of fragmentation on population genetic health provides a robust basis for strategic planning and conservation of this critically endangered species, including establishment of an ex situ population and genetic rescue through population augmentation. These methods are easily applicable and particularly relevant to other plant species with small populations or those occurring in fragmented systems.

Effects of DNA degradation and genotype imputation on high-density SNP microarray in pairwise kinship analysis

High-density single nucleotide polymorphisms (SNPs) can detect distant relatives even in the context of pairwise kinship analysis. Although DNA microarrays conveniently generate genome-wide SNP data, they require large quantities of high-quality DNA. Genotyping data obtained from low-quantity and low-quality samples are likely unreliable owing to the incidence of no-called or mistyped SNPs. In this study, we examined the effects of insufficient sample densities and sample degradation on the efficacy of kinship analysis. While low DNA amounts had a minor effect, DNA degradation led to a significant increase in no-call rates and error rates. Posterior probabilities of kinship determination, calculated using the index of chromosomal sharing, were markedly lower in proportion to the no-call rates and error rates. We also investigated the effect of genotype imputation to complement the no-called genome data utilizing SNPs reference panels. We found that the posterior probability of the relative-assumed person increased with genotype complementation in case of mild degradation, even with mistyped genotypes. Therefore, DNA microarray with imputation is a promising method for analyzing forensic DNA samples taken from situations where DNA quantity and quality may be compromised, such as disaster victim identification using pairwise kinship analysis.

Paternal half-sisters or unrelated – How can the X-chromosomal evidence be quantified when one female presents trisomy X?

The X chromosome has unique features, such as haplodiploid mode of genetic transmission, which can be crucial to complement autosomal profiling or to disentangle complex kinship problems. Indeed, for some cases (e.g. full- or paternal half-sisters, or paternal grandmother-granddaughter hypotheses), X-markers are expected to provide a similar or a higher power to the one obtained with autosomes in paternity/maternity investigations. Both theoretical and informatics frameworks for pairwise X-linked kinship analyses are well established for individuals with a regular number of chromosomes, but these are still lacking for individuals exhibiting an X chromosome aneuploidy, such as females with Triple X (47, XXX) syndrome. Indeed, this work was motivated by a real forensic case involving the evaluation with X-chromosomal markers of the hypotheses that two women were related either as paternal half-sisters or as unrelated, one of them showing a trisomy X. In this case, the analysis of X-chromosomal markers would yield stronger results than autosomes, as females had to share at least one identical allele in each analyzed X chromosome marker under the paternal half-sibling hypothesis, unless a mutation occurs. To fulfill this gap, we present in this work algebraic formulae for some genotypic configurations, which will allow quantification of the evidence on the referred cases. A general approach, comprising other X chromosome aneuploidies, kinship hypotheses, and genotypic configurations, is currently being developed by us. This work is the starting point to analyze X-chromosomal data under the scope of kinship problems, involving individuals with aneuploidies. This will improve the quantification of DNA evidence not only in forensic casework, but also in the field of medical genetics, whenever individuals with X-chromosomal aneuploidies are involved.

Genetic Diversity, Population Structure and Linkage Disequilibrium Analyses in Tropical Maize Using Genotyping by Sequencing.

Several maize breeding programs in India have developed numerous inbred lines but the lines have not been characterized using high-density molecular markers. Here, we studied the molecular diversity, population structure, and linkage disequilibrium (LD) patterns in a panel of 314 tropical normal corn, two sweet corn, and six popcorn inbred lines developed by 17 research centers in India, and 62 normal corn from the International Maize and Wheat Improvement Center (CIMMYT). The 384 inbred lines were genotyped with 60,227 polymorphic single nucleotide polymorphisms (SNPs). Most of the pair-wise relative kinship coefficients (58.5%) were equal or close to 0, which suggests the lack of redundancy in the genomic composition in the majority of inbred lines. Genetic distance among most pairs of lines (98.3%) varied from 0.20 to 0.34 as compared with just 1.7% of the pairs of lines that differed by <0.20, which suggests greater genetic variation even among sister lines. The overall average of 17% heterogeneity was observed in the panel indicated the need for further inbreeding in the high heterogeneous genotypes. The mean nucleotide diversity and frequency of polymorphic sites observed in the panel were 0.28 and 0.02, respectively. The model-based population structure, principal component analysis, and phylogenetic analysis revealed three to six groups with no clear patterns of clustering by centers-wise breeding lines, types of corn, kernel characteristics, maturity, plant height, and ear placement. However, genotypes were grouped partially based on their source germplasm from where they derived.

Average kinship within bighorn sheep populations is associated with connectivity, augmentation, and bottlenecks

AbstractUnderstanding the influence of population attributes on genetic diversity is important to advancement of biological conservation. Because bighorn sheep (Ovis canadensis) populations vary in size and management history, the species provides a unique opportunity to observe the response of average pairwise kinship, inversely related to genetic diversity, to a spectrum of natural and management influences. We estimated average pairwise kinship of bighorn sheep herds and compared estimates with population origin (native/indigenous/extant or reintroduced), historical minimum count, connectivity, and augmentation history, to determine which predictors were the most important. We evaluated 488 bighorn sheep from 19 wild populations with past minimum counts of 16–562 animals, including native and reintroduced populations that received 0–165 animals in augmentations. Using the Illumina High Density Ovine array, we generated a dataset of 7728 single nucleotide polymorphisms and calculated average pairwise kinship for each population. Multiple linear regression analysis determined that connectivity between populations via dispersal, greater number of animals received in augmentations, and greater minimum count were correlated with lower average pairwise kinship at the population level, and whether the population was extant or reintroduced was less important. Thus, our results indicated that genetic isolation of populations can result in increased levels of inbreeding. By determining that natural and human‐assisted gene flow were likely the most important influences of average pairwise kinship at the population level, this study can serve as a benchmark for future management of bighorn sheep populations and aid in identifying populations of genetic concern to define priorities for conservation of wild populations.

Phenotypic and molecular characterization of a set of tropical maize inbred lines from a public breeding program in Brazil

BackgroundThe characterization of genetic diversity and population differentiation for maize inbred lines from breeding programs is of great value in assisting breeders in maintaining and potentially increasing the rate of genetic gain. In our study, we characterized a set of 187 tropical maize inbred lines from the public breeding program of the Universidade Federal de Viçosa (UFV) in Brazil based on 18 agronomic traits and 3,083 single nucleotide polymorphisms (SNP) markers to evaluate whether this set of inbred lines represents a panel of tropical maize inbred lines for association mapping analysis and investigate the population structure and patterns of relationships among the inbred lines from UFV for better exploitation in our maize breeding program.ResultsOur results showed that there was large phenotypic and genotypic variation in the set of tropical maize inbred lines from the UFV maize breeding program. We also found high genetic diversity (GD = 0.34) and low pairwise kinship coefficients among the maize inbred lines (only approximately 4.00 % of the pairwise relative kinship was above 0.50) in the set of inbred lines. The LD decay distance over all ten chromosomes in the entire set of maize lines with r2 = 0.1 was 276,237 kb. Concerning the population structure, our results from the model-based STRUCTURE and principal component analysis methods distinguished the inbred lines into three subpopulations, with high consistency maintained between both results. Additionally, the clustering analysis based on phenotypic and molecular data grouped the inbred lines into 14 and 22 genetic divergence clusters, respectively.ConclusionsOur results indicate that the set of tropical maize inbred lines from UFV maize breeding programs can comprise a panel of tropical maize inbred lines suitable for a genome-wide association study to dissect the variation of complex quantitative traits in maize, mainly in tropical environments. In addition, our results will be very useful for assisting us in the assignment of heterotic groups and the selection of the best parental combinations for new breeding crosses, mapping populations, mapping synthetic populations, guiding crosses that target highly heterotic and yielding hybrids, and predicting untested hybrids in the public breeding program UFV.

Pairwise kinship analysis of 17 pedigrees using massively parallel sequencing

With the tremendous development of massively parallel sequencing (MPS) in the last decade, it has been widely applied in basic science, clinical diagnostics, microbial genomics, as well as forensic genetics. MPS has lots of advantages that may facilitate the kinship analysis. In this study, 243 Chinese Han individuals from 17 families were involved and sequenced using the ForenSeq™ DNA Signature Prep Kit (Verogen, Inc., San Diego, USA), which provided the sequence information of 27 autosomal STRs (A-STRs), 7 X chromosomal STRs (X-STRs), 24 Y chromosomal STRs (Y-STRs) and 94 identity-informative SNPs (iSNPs). A total of 275 pairs of parent-child, 123 pairs of full siblings, 1 pair of twins, 1 pair of half siblings, 158 pairs of grandparent-grandchild, 222 pairs of uncle/aunt-nephew/niece and 121 pairs of first cousins, as well as 701 pairs of unrelated individuals were identified. Using both likelihood ratio (LR) and identical by state (IBS) methods, the kinship analysis was conducted among these relative and non-relative pairs based on the A-STRs and SNPs. As a result, the ForenSeq Signature Kit could solve the analysis of parent-child (t1 = −4, t2 = 4), full siblings (t1 = −2, t2 = 2) and most second-degree kinships (t1 = −1, t2 = 1) using the LR method. When the IBS method was applied, 123 full sibling pairs had a higher average IBS value than other kinship groups in this study. And the IBS method could play a role in the testing of parent-child and full siblings.

Pairwise kinship testing with microhaplotypes: Can advancements be made in kinship inference with these markers?

Kinship testing based on genetic relatedness is one of the major tasks in forensic genetics. Although short tandem repeats (STRs) are the “gold standard” biomarkers for relationship testing, microhaplotypes (MHs) have also emerged as viable options for kinship elucidation. In this work, the kinship testing efficiency of 54 highly polymorphic MHs was studied in two extended families consisting of parent-offspring, full siblings, grandparent-grandchildren, uncle/aunt-nephew/nieces, and first cousins. In addition, ten-thousand pairs of different degrees of relationships were simulated using various datasets including 54 MHs, 27 STRs plus 94 single nucleotide polymorphisms (SNPs) that were included in the ForenSeq DNA Signature Prep Kit (ForenSeq), 54 MHs plus loci in ForenSeq, and different subsets of 417-published MHs. The panels’ system effectiveness in the kinship analysis were accessed by likelihood ratio distributions. The results showed that 54 MHs could be used in first-degree relationship testing with high reliability. The effectiveness of 54 MHs was slightly lower than ForenSeq but only by a narrow margin. Both 54 MHs and ForenSeq were not sufficient for distant relationship testing, and approximately 200 microhaplotypes with an average expected heterozygosity (He) = 0.79 were enough to determine second-degree relationships, but a panel of 417 MHs with an average He = 0.72 was not sufficient to first cousins testing according to the simulation analysis. In conclusion, 54 MHs could be used to serve as supplement markers for kinship testing; and well-established STR markers plus well-performing microhaplotype markers may become collective tools in forensic applications, though an enlarged pool of forensic markers is needed for distant relationship testing.

Genome-wide survey of parent-of-origin-specific associations across clinical traits derived from electronic health records.

SummaryParent-of-origin (PoO) effects refer to the differential phenotypic impacts of genetic variants dependent on their parental inheritance due to imprinting. While PoO effects can influence complex traits, they may be poorly captured by models that do not differentiate the parental origin of the variant. The aim of this study was to conduct a genome-wide screen for PoO effects on a broad range of clinical traits derived from electronic health records (EHR) in the DiscovEHR study enriched with familial relationships. Using pairwise kinship estimates from genetic data and demographic data, we identified 22,051 offspring among 134,049 individuals in the DiscovEHR study. PoO of ~9 million variants was assigned in the offspring by comparing offspring and parental genotypes and haplotypes. We then performed genome-wide PoO association analyses across 154 quantitative and 611 binary traits extracted from EHR. Of the 732 significant PoO associations identified (p < 5 × 10−8), we attempted to replicate 274 PoO associations in the UK Biobank study with 5,015 offspring and replicated 9 PoO associations (p < 0.05). In summary, our study implements a bioinformatic and statistical approach to examine PoO effects genome-wide in a large population study enriched with familial relationships and systematically characterizes PoO effects on hundreds of clinical traits derived from EHR. Our results suggest that, while the statistical power to detect PoO effects remains modest yet, accurately modeling PoO effects has the potential to find new associations that may have been missed by the standard additive model, further enhancing the mechanistic understanding of genetic influence on complex traits.

Genetic variation and population structure in China summer maize germplasm

Maize (Zea mays L.) germplasm in China Summer maize ecological region (CSM) or central corn-belt of China is diverse but has not been systematically characterized at molecular level. In this study, genetic variation, genome diversity, linkage disequilibrium patterns, population structure, and characteristics of different heterotic groups were studied using 525,141 SNPs obtained by Genotyping-By-Sequencing (GBS) for 490 inbred lines collected from researchers at CSM region. The SNP density is lower near centromere, but higher near telomere region of maize chromosome, the degree of linkage disequilibrium (r2) vary at different chromosome regions. Majority of the inbred lines (66.05%) show pairwise relative kinship near zero, indicating a large genetic diversity in the CSM breeding germplasm. Using 4849 tagSNPs derived from 3618 haplotype blocks, the 490 inbred lines were delineated into 3 supergroups, 6 groups, and 10 subgroups using ADMIXTURE software. A procedure of assigning inbred lines into heterotic groups using genomic data and tag-SNPs was developed and validated. Genome differentiation among different subgroups measured by Fst, and the genetic diversity within each subgroup measured by GD are both large. The share of heterotic groups that have significant North American germplasm contribution: P, SS, IDT, and X, accounts about 54% of the CSM breeding germplasm collection and has increased significantly in the last two decades. Two predominant types of heterotic pattern in CSM region are: M-Reid group × TSPT group, and X subgroup × Local subgroups.

AUCP: An indicator for system effectiveness of panels in pairwise distant kinship identification

Multiple studies have been done for the identification of pairwise distant kinship and several targeted panels have been constructed. For most of such constructions, pedigree analysis was applied to evaluate the system effectiveness of a certain panel. However, such analyses were hard to be compared to each other and could be affected by many factors, such as sample size and sampling randomness. A new indicator named predicted area under ROC curve (AUCP), where ROC curve stood for receiver operating characteristic curve, was derived applying binomial distribution theory and analyzed with simulated and real cases in this study. After comparing between the values of AUCPs and results of pedigree analyses with different loci sets and kinship types, the ability of these two methods evaluating the system effectiveness was proved to be close to each other. The implementation of AUCP was much easier than pedigree analysis, because a secondary sampling or simulation was not needed. Therefore, AUCP can be a better indicator for panels targeted to pairwise distant kinship identification and we are recommending it as an indicator calculated by default for such panels.

IBDkin: fast estimation of kinship coefficients from identity by descent segments.

Estimation of pairwise kinship coefficients in large datasets is computationally challenging because the number of related individuals increases quadratically with sample size. We present IBDkin, a software package written in C for estimating kinship coefficients from identity by descent (IBD) segments. We use IBDkin to estimate kinship coefficients for 7.95 billion pairs of individuals in the UK Biobank who share at least one detected IBD segment with length ≥ 4 cM. https://github.com/YingZhou001/IBDkin. Supplementary data are available at Bioinformatics online.

Pairwise kinship testing with a combination of STR and SNP loci

Individual commercially available kits exhibit limited discrimination power in full-sibling and second-degree kinship analysis, and therefore they are commonly combined with other kits to obtain more loci and a higher efficacy. However, few studies have systematically evaluated the discrimination power of combined loci. In this study, we combined the ForenSeq™ DNA Signature kit (containing 27 short tandem repeats [STRs] + 91 single nucleotide polymorphisms [SNPs]) with the AGCU NC 21 + 1 PCR amplification kit (containing 21 STRs) to obtain a non-overlapping set of 40 STR and 91 SNP markers. The discrimination power was evaluated for 74 full-sibling pairs, 114 uncle/aunt-nephew/niece pairs and 93 grandparent-grandson/granddaughter pairs. The results show that the efficacy of the 40 STR + 91 SNP combination is higher than the efficacy of either 27 STRs + 91 SNPs or 40 STRs alone. Both the sensitivity and specificity of the 40 STR + 91 SNP marker set achieved 100 % in full-sibling testing, with strong power to distinguish second-degree relatives from unrelated pairs. The 40 STR + 91 SNP set could also distinguish most full-sibling relatives from second-degree relatives but was insufficient to distinguish relatives who belong to the same autosomal kinship class. Our results suggest that ignoring linkage can lead to incorrect likelihood ratios for both related and unrelated pairs, while mutation had a relatively lower effect on the likelihood ratios. Moreover, linkage and mutation had a higher impact on full-sibling testing than on second-degree kinship testing. The discrimination power of the 40 STR and 91 SNP marker set could be strengthened by adding an additional relative.