Haplotype mining panel for genetic dissection and breeding in Eucalyptus.

To improve our understanding of genetic mechanisms underlying complex traits in plants, a comprehensive analysis of gene variants is required. Eucalyptus is an important forest plantation genus that is highly outbred. Trait dissection and molecular breeding in eucalypts currently relies on biallelic single-nucleotide polymorphism (SNP) markers. These markers fail to capture the large amount of haplotype diversity in these species, and thus multi-allelic markers are required. We aimed to develop a gene-based haplotype mining panel for Eucalyptus species. We generated 17 999 oligonucleotide probe sets for targeted sequencing of selected regions of 6293 genes implicated in growth and wood properties, pest and disease resistance, and abiotic stress responses. We identified and phased 195 834 SNPs using a read-based phasing approach to reveal SNP-based haplotypes. A total of 8915 target regions (at 4637 gene loci) passed tests for Mendelian inheritance. We evaluated the haplotype panel in four Eucalyptus species (E. grandis, E. urophylla, E. dunnii and E. nitens) to determine its ability to capture diversity across eucalypt species. This revealed an average of 3.13-4.52 haplotypes per target region in each species, and 33.36% of the identified haplotypes were shared by at least two species. This haplotype mining panel will enable the analysis of haplotype diversity within and between species, and provide multi-allelic markers that can be used for genome-wide association studies and gene-based breeding approaches.

Development of a 39 MM-InDel multiplex assay for the forensic application.

Insertion/deletion polymorphisms (InDels) are a category of highly prevalent markers in the human genome, characterized by their distinctive attributes, including short amplicon sizes and low mutation rates, which have shown great potential in forensic applications. Multi-allelic InDel and multi-InDel markers, collectively abbreviated as MM-InDels, were developed to enhance polymorphism by the introduction of novel alleles. Nevertheless, the relatively low mutation rates of InDels, coupled with the founder effect, result in distinct allele frequency distributions among populations. The divergent characteristics of InDels in different populations also pose challenges to the establishment of universally efficient InDel multiplex assays. To enhance the system efficiency of the InDel assay and its applicability across diverse populations, 39 MM-InDels with high polymorphism in five different ancestry superpopulations were selected from the 1000 Genomes Project dataset and combined with an amelogenin gender marker to construct a multiplex assay (named MMIDplex). The combined power of discrimination and the cumulative probability of exclusion of 39 MM-InDels were 1 - 1.3 × 10-23 and 1 - 9.83 × 10-6 in the Chinese Han population, and larger than 1-10-19 and 1-10-4 in the reference populations, relatively. These results demonstrate that the MMIDplex assay has the potential to obtain sufficient power for individual identification and paternity test in global populations.

Development of a multiplex panel with 31 multi-allelic InDels for forensic DNA typing.

Insertion/Deletion (InDel) polymorphic genetic markers are abundant in human genomes. Diallelic InDel markers have been widely studied for forensic purposes, yet the low polymorphic information content limits their application and current InDel panels remain to be improved. In this study, multi-allelic InDels located out of low complexity sequence regions were selected in the datasets from East Asian populations, and a multiplex amplification system containing 31 multi-allelic InDel markers and the Amelogenin marker (FA-HID32plex) was constructed and optimized. The preliminary study on sensitivity, species specificity, inhibitor tolerance, mixture resolution, and the detection of degraded samples demonstrates that the FA-HID32plex is highly sensitive, specific, and robust for traces and degraded samples. The combined power of discrimination (CPD) of 31 multi-allelic InDel markers was 0.999 999 999 999 999 999 85, and the cumulative probability of exclusion (CPE) was 0.999 920 in a Chinese Han population, which indicates a high discrimination power. Altogether, the FA-HID32plex panel could provide reliable supplements or stand-alone information in individual identification and paternity testing, especially for challenging samples.

PolyHaplotyper: haplotyping in polyploids based on bi-allelic marker dosage data.

BACKGROUND: For genetic analyses, multi-allelic markers have an advantage over bi-allelic markers like SNPs (single nucleotide polymorphisms) in that they carry more information about the genetic constitution of individuals. This is especially the case in polyploids, where individuals carry more than two alleles at each locus. Haploblocks are multi-allelic markers that can be derived by phasing sets of closely-linked SNP markers. Phased haploblocks, similarly to other multi-allelic markers, will therefore be advantageous in genetic tasks like linkage mapping, QTL mapping and genome-wide association studies. RESULTS: We present a new method to reconstruct haplotypes from SNP dosages derived from genotyping arrays, which is applicable to polyploids. This method is implemented in the software package PolyHaplotyper. In contrast to existing packages for polyploids it makes use of full-sib families among the samples to guide the haplotyping process. We show that in this situation it is much more accurate than other available software, using experimental hexaploid data and simulated tetraploid data. CONCLUSIONS: Our method and the software package PolyHaplotyper in which it is implemented extend the available tools for haplotyping in polyploids. They perform especially well in situations where one or more full-sib families are present.

Development a multiplex panel of AISNPs, multi-allelic InDels, microhaplotypes, and Y-SNP/InDel loci for multiple forensic purposes via the NGS.

Recently, next generation sequencing has shown the promising application value in forensic research. In this study, we constructed a multiplex amplification system of different molecular genetic markers based on the previous selected ancestry informative single nucleotide polymorphisms (SNPs), multi-allelic insertion/deletion (InDel) polymorphisms, microhaplotypes, and Y-chromosomal SNP/InDel loci, and evaluated forensic efficiencies of the system in Chinese Shaanxi Han, Chinese Hui, and Chinese Mongolian groups via the next generation sequencing platform. Ancestry information analyses of Shaanxi Han, Hui, and Mongolian groups revealed that most Mongolian individuals could be differentiated from Shaanxi Hans and Huis based on the selected ancestry informative SNPs. Multi-allelic InDels and microhaplotypes showed the multiple allele variations and possessed relatively high genetic polymorphisms in these three groups, indicating these loci could provide higher forensic efficiencies for individual identification and paternity testing. Based on Y-chromosomal SNPs, different haplogroup distributions were observed among Shaanxi Han, Hui, and Mongolian groups. In conclusion, the self-developed system could be used to simultaneously carry out the individual identification, paternity analysis, mixture deconvolution, forensic ancestry information analysis, and Y-chromosomal haplogroup inference, which could provide more valuable investigative clues in forensic practices.

A set of novel multi-allelic SNPs for forensic application developed through massively parallel sequencing and its examples of population genetic studies.

Massively parallel sequencing (MPS) technology allows to simultaneously type multitudinous molecular genetic markers for many samples in one run with the feature of high detection resolution, and thereby arouses the increasing attention from forensic science. Herein, multiple allelic single nucleotide polymorphisms (multi-allelic SNPs) were screened for personal identification and parentage testing, and then were genotyped using MPS platform. Unrelated individuals of Chinese Mongolian and Kazakh groups were investigated to further estimate forensic effectiveness and applicability of these multi-allelic SNPs. The results of sequencing efficiency estimations and forensic genetic statistical parameters demonstrated that this MPS panel of multi-allelic SNPs was expected to be work for forensic applications. Subsequently, the exploration of population genetic variation patterns among the two investigated groups and other 26 reference populations revealed that these Chinese Mongolian and Kazakh groups had the similar population genetic patterns with the populations from East Asian, but European ancestral composition in the Kazakh group was higher than that in the Mongolian group. Currently, the present results were the preliminary research to scrutinize genetic information of these two ethnic minority groups employing multi-allelic SNPs.

Multi-allelic positional Burrows-Wheeler transform.

BACKGROUND: Recent advances in whole-genome sequencing and SNP array technology have led to the generation of a large amount of genotype data. Large volumes of genotype data will require faster and more efficient methods for storing and searching the data. Positional Burrows-Wheeler Transform (PBWT) provides an appropriate data structure for bi-allelic data. With the increasing sample sizes, more multi-allelic sites are expected to be observed. Hence, there is a necessity to handle multi-allelic genotype data. RESULTS: In this paper, we introduce a multi-allelic version of the Positional Burrows-Wheeler Transform (mPBWT) based on the bi-allelic version for compression and searching. The time-complexity for constructing the data structure and searching within a panel containing t-allelic sites increases by a factor of t. CONCLUSION: Considering the small value for the possible alleles t, the time increase for the multi-allelic PBWT will be negligible and comparable to the bi-allelic version of PBWT.

MinION sequencing to genotype US strains of infectious laryngotracheitis virus.

Over the last decade the US broiler industry has fought long-lasting outbreaks of infectious laryngotracheitis (ILTV). Previously, nine genotypes (I-IX) of ILTVs have been recognized using the polymerase chain reaction-restriction fragment length polymorphisms (PCR-RFLP) method with three viral alleles (gB, gM and UL47/gG). In this study, the genotyping system was simplified to six genotypes by amplicon sequencing and examining discriminating single nucleotide polymorphisms (SNPs) within these open reading frames. Using phylogenomic analysis of 27 full genomes of ILTV, a single allele (ORF A/ORF B) was identified containing SNPs that could differentiate ILTVs into genotypes congruent with the phylogenetic partitioning. The allelic variations allowed for the cataloging of the 27 strains into 5 genotypes: vaccinal TCO, vaccinal CEO, virulent CEO-like, virulent US and virulent US backyard flocks from 1980 to 1990, correlating with the PCR-RFLP genotypes I/ II/ III (TCO), IV (CEO), V (virulent CEO-like), VI (virulent US) and VII/VIII/IX (virulent US backyard flock isolates). With the unique capabilities of third generation sequencing, we investigated the application of Oxford Nanopore MinION technology for rapid sequencing of the amplicons generated in the single-allele assay. This technology was an improvement over Sanger-based sequencing of the single allele amplicons due to a booster amplification step in the MinION sequencing protocol. Overall, there was a 90% correlation between the genotyping results of the single-allele assay and the multi-allele assay. Surveillance of emerging ILTV strains could greatly benefit from real-time amplicon sequencing using the single-allele assay and MinION sequencing. RESEARCH HIGHLIGHTS A multi-allelic assay identified nine ILTV genotypes circulating in the US Single-allele genotyping is congruent with whole genome phylogenetic partitioning US ILTV strains can be grouped into five genotypes using the single-allele assay The single-allele assay can be done using MinION sequencing of barcoded amplicons.

A general framework for moment-based analysis of genetic data.

In population genetics, the Dirichlet (also called the Balding-Nichols) model has for 20 years been considered the key model to approximate the distribution of allele fractions within populations in a multi-allelic setting. It has often been noted that the Dirichlet assumption is approximate because positive correlations among alleles cannot be accommodated under the Dirichlet model. However, the validity of the Dirichlet distribution has never been systematically investigated in a general framework. This paper attempts to address this problem by providing a general overview of how allele fraction data under the most common multi-allelic mutational structures should be modeled. The Dirichlet and alternative models are investigated by simulating allele fractions from a diffusion approximation of the multi-allelic Wright-Fisher process with mutation, and applying a moment-based analysis method. The study shows that the optimal modeling strategy for the distribution of allele fractions depends on the specific mutation process. The Dirichlet model is only an exceptionally good approximation for the pure drift, Jukes-Cantor and parent-independent mutation processes with small mutation rates. Alternative models are required and proposed for the other mutation processes, such as a Beta-Dirichlet model for the infinite alleles mutation process, and a Hierarchical Beta model for the Kimura, Hasegawa-Kishino-Yano and Tamura-Nei processes. Finally, a novel Hierarchical Beta approximation is developed, a Pyramidal Hierarchical Beta model, for the generalized time-reversible and single-step mutation processes.

PyHLA: tests for the association between HLA alleles and diseases.

BACKGROUND: Recently, several tools have been designed for human leukocyte antigen (HLA) typing using single nucleotide polymorphism (SNP) array and next-generation sequencing (NGS) data. These tools provide high-throughput and cost-effective approaches for identifying HLA types. Therefore, tools for downstream association analysis are highly desirable. Although several tools have been designed for multi-allelic marker association analysis, they were designed only for microsatellite markers and do not scale well with increasing data volumes, or they were designed for large-scale data but provided a limited number of tests. RESULTS: We have developed a Python package called PyHLA, which implements several methods for HLA association analysis, to fill the gap. PyHLA is a tailor-made, easy to use, and flexible tool designed specifically for the association analysis of the HLA types imputed from genome-wide genotyping and NGS data. PyHLA provides functions for association analysis, zygosity tests, and interaction tests between HLA alleles and diseases. Monte Carlo permutation and several methods for multiple testing corrections have also been implemented. CONCLUSIONS: PyHLA provides a convenient and powerful tool for HLA analysis. Existing methods have been integrated and desired methods have been added in PyHLA. Furthermore, PyHLA is applicable to small and large sample sizes and can finish the analysis in a timely manner on a personal computer with different platforms. PyHLA is implemented in Python. PyHLA is a free, open source software distributed under the GPLv2 license. The source code, tutorial, and examples are available at https://github.com/felixfan/PyHLA.

PPARG-LYPLAL1 Multi-Allelic Combination Associated with Obesity and Overweight in Mexican Adolescent Females.

OBJECTIVE: We studied multi-loci variants to identify the contribution of six candidate genes (ADIPOQ, CDH13, LYPLAL1, MC4R, PPARG and PGC1A) in the development of obesity and overweight. DESIGN: We genotyped 404 chromosomes with eleven SNPs in Mexican female adolescents, who were subdivided into two groups (obesity-overweight and normal-weight) using the World Health Organization parameters. Genomic (800 chromosomes) and ancestral (208 chromosomes) controls were included to reduce the population bias. Anthropometric measurements, biochemical parameters, and caloric intake were obtained only in the groups of Mexican female adolescents. RESULTS: A positive genotype-phenotype association was found that involves the multi-allelic combination of three risk alleles (one in PPARG and two in LYPLAL1) with obesity and overweight (OR=3.1, P=.010). This combination also exhibited a significant association with waist circumference (P=.030) and triglycerides levels (P=.030). These associations were supported by a logistic regression analysis adjusted for several confounding variables. CONCLUSIONS: Our data suggest the joint participation of PPARG-LYPLAL1 genes in metabolic disorders development. Hence, these genes could act as potential biomarkers in obesity and overweight. Our findings underscore the complexity of metabolic disorders and provide evidence about the importance of multi-loci analysis to study complex diseases.

Assessing Autosomal InDel Loci With Multiple Insertions or Deletions of Random DNA Sequences in Human Genome.

Multiple mutational events of insertion/deletion occurring at or around InDel sites could form multi-allelic InDels and multi-InDels (abbreviated as MM-InDels), while InDels with random DNA sequences could imply a unique mutation event at these loci. In this study, preliminary investigation of MM-InDels with random sequences was conducted using high-throughput phased data from the 1000 Genomes Project. A total of 3,599 multi-allelic InDels and 6,375 multi-InDels were filtered with multiple alleles. A vast majority of the obtained MM-InDels (85.59%) presented 3 alleles, which implies that only one secondary insertion or deletion mutation event occurred at these loci. The more frequent presence of two adjacent InDel loci was observed within 20 bp. MM-InDels with random sequences presented an uneven distribution across the genome and showed a correlation with InDels, SNPs, recombination rate, and GC content. The average allelic frequencies and prevalence of multi-allelic InDels and multi-InDels presented similar distribution patterns in different populations. Altogether, MM-InDels with random sequences can provide useful information for population resolution.

Dynamic Programming for Resource Allocation in Multi-Allelic Trait Introgression.

Trait introgression is a complex process that plant breeders use to introduce desirable alleles from one variety or species to another. Two of the major types of decisions that must be made during this sophisticated and uncertain workflow are: parental selection and resource allocation. We formulated the trait introgression problem as an engineering process and proposed a Markov Decision Processes (MDP) model to optimize the resource allocation procedure. The efficiency of the MDP model was compared with static resource allocation strategies and their trade-offs among budget, deadline, and probability of success are demonstrated. Simulation results suggest that dynamic resource allocation strategies from the MDP model significantly improve the efficiency of the trait introgression by allocating the right amount of resources according to the genetic outcome of previous generations.

Association Analysis and Meta-Analysis of Multi-Allelic Variants for Large-Scale Sequence Data.

There is great interest in understanding the impact of rare variants in human diseases using large sequence datasets. In deep sequence datasets of >10,000 samples, ~10% of the variant sites are observed to be multi-allelic. Many of the multi-allelic variants have been shown to be functional and disease-relevant. Proper analysis of multi-allelic variants is critical to the success of a sequencing study, but existing methods do not properly handle multi-allelic variants and can produce highly misleading association results. We discuss practical issues and methods to encode multi-allelic sites, conduct single-variant and gene-level association analyses, and perform meta-analysis for multi-allelic variants. We evaluated these methods through extensive simulations and the study of a large meta-analysis of ~18,000 samples on the cigarettes-per-day phenotype. We showed that our joint modeling approach provided an unbiased estimate of genetic effects, greatly improved the power of single-variant association tests among methods that can properly estimate allele effects, and enhanced gene-level tests over existing approaches. Software packages implementing these methods are available online.

Identification of extra alleles in DYS385a/b multi-allelic patterns.

Y chromosome short tandem repeats (Y-STRs) are widely used in forensic DNA analysis. Y-STRs usually genotyped as a monoallelic pattern, or a diallelic pattern at some double-copy loci. Abnormal genotypes with three or four alleles have been reported at DYS385a/b, which is a double-copy locus. However, multi-allelic patterns with more than four alleles have not been reported at this locus. In this study, abnormal five-allelic patterns at DYS385a/b locus were observed in 2 out of 7760 unrelated males from Henan Province, detected by the HG19+14Y fluorescence detection kit; and abnormal six-allelic pattern was observed in 1 out of 4920 unrelated males from Guangdong Province, detected by the AGCU Data Y30 fluorescence kit. The genotypes of these abnormal samples were confirmed again by the Yfiler® Plus and PowerPlex® Y23 kits. In order to understand the genomic structure of the extra alleles at this locus, forward and reverse primers were designed to sequence the three samples. The results showed that the five-banded and six-banded pattern genotype did exist at DYS385a/b locus. These data enriched the knowledge about multi-allelic patterns at DYS385a/b locus, which allowed the use of DYS385a/b profile in forensic analysis, even with multi-allelic patterns.

Analysis of Variance Components for Genetic Markers with Unphased Genotypes.

An ANOVA type general multi-allele (GMA) model was proposed in Wang (2014) on analysis of variance components for quantitative trait loci or genetic markers with phased or unphased genotypes. In this study, by applying the GMA model, we further examine estimation of the genetic variance components for genetic markers with unphased genotypes based on a random sample from a study population. In one locus and two loci cases, we first derive the least square estimates (LSE) of model parameters in fitting the GMA model. Then we construct estimators of the genetic variance components for one marker locus in a Hardy-Weinberg disequilibrium population and two marker loci in an equilibrium population. Meanwhile, we explore the difference between the classical general linear model (GLM) and GMA based approaches in association analysis of genetic markers with quantitative traits. We show that the GMA model can retain the same partition on the genetic variance components as the traditional Fisher's ANOVA model, while the GLM cannot. We clarify that the standard F-statistics based on the partial reductions in sums of squares from GLM for testing the fixed allelic effects could be inadequate for testing the existence of the variance component when allelic interactions are present. We point out that the GMA model can reduce the confounding between the allelic effects and allelic interactions at least for independent alleles. As a result, the GMA model could be more beneficial than GLM for detecting allelic interactions.

Complex and multi-allelic copy number variation in human disease.

Hundreds of copy number variants are complex and multi-allelic, in that they have many structural alleles and have rearranged multiple times in the ancestors who contributed chromosomes to current humans. Not only are the relationships of these multi-allelic CNVs (mCNVs) to phenotypes generally unknown, but many mCNVs have not yet been described at the basic levels-alleles, allele frequencies, structural features-that support genetic investigation. To date, most reported disease associations to these variants have been ascertained through candidate gene studies. However, only a few associations have reached the level of acceptance defined by durable replications in many cohorts. This likely stems from longstanding challenges in making precise molecular measurements of the alleles individuals have at these loci. However, approaches for mCNV analysis are improving quickly, and some of the unique characteristics of mCNVs may assist future association studies. Their various structural alleles are likely to have different magnitudes of effect, creating a natural allelic series of growing phenotypic impact and giving investigators a set of natural predictions and testable hypotheses about the extent to which each allele of an mCNV predisposes to a phenotype. Also, mCNVs' low-to-modest correlation to individual single-nucleotide polymorphisms (SNPs) may make it easier to distinguish between mCNVs and nearby SNPs as the drivers of an association signal, and perhaps, make it possible to preliminarily screen candidate loci, or the entire genome, for the many mCNV-disease relationships that remain to be discovered.

An MLPA-based approach for high-resolution genotyping of disease-related multi-allelic CNVs.

Copy number variation has recently been recognized as an important type of genetic variation that modifies human phenotypes. Copy number variants (CNVs) are being increasingly associated with various human phenotypes and diseases. However, the lack of an appropriate method that allows fast, inexpensive and, most importantly, accurate CNVs genotyping significantly hampers CNV analysis. This limitation especially affects the analysis of multi-allelic CNVs that frequently modify various phenotypes. Recently, we developed a multiplex ligation-dependent probe amplification (MLPA)-based strategy for multiplex copy number genotyping and the validation of candidate CNV-miRNAs. Here we present the adaptation and optimization of this recently developed method for high-resolution genotyping of individual disease-related multi-allelic CNVs. We developed appropriate assays for three well-known and extensively studied CNVs: CNV-CCL3L1, CNV-DEFB, and CNV-UGT2B17, which have been associated with various human phenotypes including inflammation-related and infectious diseases. With the use of these assays we identified several general factors that allow to increase the resolution of the copy number genotyping. Performed experiments confirmed the high reproducibility and accuracy of the obtained genotyping results. The reliability of the results and relatively low per-genotype cost makes this strategy an attractive method for large-scale experiments such as genotype-phenotype association studies.

Identification of the predominant nonrestoring allele for Owen-type cytoplasmic male sterility in sugar beet (Beta vulgaris L.): development of molecular markers for the maintainer genotype.

Hybrid seed production in sugar beet relies on cytoplasmic male sterility (CMS). As time-consuming and laborious test crosses with a CMS tester are necessary to identify maintainer lines, development of a marker-assisted selection method for the rf gene (the nonrestoring allele of restorer-of-fertility locus) is highly desirable for sugar-beet breeding. To develop such a method, we investigated genetic variation at the Rf1 locus, one of two Rf loci known in sugar beet. After HindIII-digestion, genomic DNAs from beet plants known to have a restoring Rf1 allele yielded a range of hybridization patterns on agarose gels, indicating that Rf1 is a multi-allelic locus. However, the hybridization patterns of 22 of 23 maintainer lines were indistinguishable. The nucleotide sequences of the rf1 coding regions of these 22 maintainer lines were found to be identical, confirming that the lines had the same rf1 allele. Two PCR markers were developed that targeted a downstream intergenic sequence and an intron of Rf1. The electrophoretic patterns of both markers indicated multiple Rf1 alleles, one of which, named the dd(L) type, was associated with the maintainer genotype. To test the validity of marker-assisted selection, 147 sugar beet plants were genotyped using these markers. Additionally, the 147 sugar beet plants were crossed with CMS plants to determine whether they possessed the maintainer genotype. Analysis of 5038 F1 offspring showed that 53 % of the dd(L) plants, but none of the plants with other alleles, had the maintainer genotype. Thus, selection for the dd(L) type considerably enriched the proportion of plants with the maintainer genotype.