Haplotype Estimation Using Sequencing Reads

High-throughput sequencing technologies produce short sequence reads that can contain phase information if they span two or more heterozygote genotypes. This information is not routinely used by current methods that infer haplotypes from genotype data. We have extended the SHAPEIT2 method to use phase-informative sequencing reads to improve phasing accuracy. Our model incorporates the read information in a probabilistic model through base quality scores within each read. The method is primarily designed for high-coverage sequence data or data sets that already have genotypes called. One important application is phasing of single samples sequenced at high coverage for use in medical sequencing and studies of rare diseases. Our method can also use existing panels of reference haplotypes. We tested the method by using a mother-father-child trio sequenced at high-coverage by Illumina together with the low-coverage sequence data from the 1000 Genomes Project (1000GP). We found that use of phase-informative reads increases the mean distance between switch errors by 22% from 274.4 kb to 328.6 kb. We also used male chromosome X haplotypes from the 1000GP samples to simulate sequencing reads with varying insert size, read length, and base error rate. When using short 100 bp paired-end reads, we found that using mixtures of insert sizes produced the best results. When using longer reads with high error rates (5–20 kb read with 4%–15% error per base), phasing performance was substantially improved.     

A fault-tolerant method for HLA typing with PacBio data

Background

Human leukocyte antigen (HLA) genes are critical genes involved in important biomedical aspects, including organ transplantation, autoimmune diseases and infectious diseases. The gene family contains the most polymorphic genes in humans and the difference between two alleles is only a single base pair substitution in many cases. The next generation sequencing (NGS) technologies could be used for high throughput HLA typing but in silico methods are still needed to correctly assign the alleles of a sample. Computer scientists have developed such methods for various NGS platforms, such as Illumina, Roche 454 and Ion Torrent, based on the characteristics of the reads they generate. However, the method for PacBio reads was less addressed, probably owing to its high error rates. The PacBio system has the longest read length among available NGS platforms, and therefore is the only platform capable of having exon 2 and exon 3 of HLA genes on the same read to unequivocally solve the ambiguity problem caused by the “phasing” issue.

Results

We proposed a new method BayesTyping1 to assign HLA alleles for PacBio circular consensus sequencing reads using Bayes’ theorem. The method was applied to simulated data of the three loci HLA-A, HLA-B and HLA-DRB1. The experimental results showed its capability to tolerate the disturbance of sequencing errors and external noise reads.

Conclusions

The BayesTyping1 method could overcome the problems of HLA typing using PacBio reads, which mostly arise from sequencing errors of PacBio reads and the divergence of HLA genes, to some extent.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-296) contains supplementary material, which is available to authorized users.     

The Tip of the “Celiac Iceberg” in China: A Systematic Review and Meta-Analysis

Objective

Until recently, celiac disease was considered to be rare in China. We aimed to estimate its true status.

Methods

By searching the MEDLINE database and four Chinese full-text databases (CNKI, CBM, VIP and WANFANG) (up to August 2012), as well as two HLA allele frequency net databases and the Chinese Statistics Yearbook databases, we systematically reviewed the literature on definite and suspected cases of celiac disease, the predisposing HLA allele frequencies, and on gluten exposure in China. Meta-analysis was performed by analyzing DQ2, DQ8 and DQB1*0201 gene frequencies and heterogeneity in populations from different geographic regions and ethnicities in China.

Results

At present, the number of reported celiac disease cases is extremely low in China. The frequencies of the HLA-DQ2.5 and HLA-DQ8 haplotypes were 3.4% (95% confidence interval 1.3–5.5%) and 2.1% (0.1–4.1%), respectively. HLA-DQ2 and HLA-DQ8 antigen frequencies were 18.4% (15.0–21.7%) and 8.0% (4.5–11.4%), respectively. The frequency of the DQB1*0201 allele was 10.5% (9.3–11.6%) and it was more common in the northern Chinese than in the southern Chinese populations. The chance of being exposed to gluten is rapidly increasing all over China nowadays.

Conclusion

The data on HLA haplotyping, in conjunction with increasing wheat consumption, strongly suggests that the occurrence of celiac disease is more common in China than currently reported. Coordinated measures by the Chinese government, medical and agricultural research institutions, and food industries, would be justified to create more awareness about celiac disease and to prevent it becoming a medical and societal burden.     

Remarkably Low KIR and HLA Diversity in Amerindians Reveals Signatures of Strong Purifying Selection Shaping the Centromeric KIR Region

The killer-cell immunoglobulin-like receptors (KIR) recognize human leukocyte antigen (HLA) molecules to regulate the cytotoxic and inflammatory responses of natural killer cells. KIR genes are encoded by a rapidly evolving gene family on chromosome 19 and present an unusual variation of presence and absence of genes and high allelic diversity. Although many studies have associated KIR polymorphism with susceptibility to several diseases over the last decades, the high-resolution allele-level haplotypes have only recently started to be described in populations. Here, we use a highly innovative custom next-generation sequencing method that provides a state-of-art characterization of KIR and HLA diversity in 706 individuals from eight unique South American populations: five Amerindian populations from Brazil (three Guarani and two Kaingang); one Amerindian population from Paraguay (Aché); and two urban populations from Southern Brazil (European and Japanese descendants from Curitiba). For the first time, we describe complete high-resolution KIR haplotypes in South American populations, exploring copy number, linkage disequilibrium, and KIR–HLA interactions. We show that all Amerindians analyzed to date exhibit the lowest numbers of KIR–HLA interactions among all described worldwide populations, and that 83–97% of their KIR–HLA interactions rely on a few HLA-C molecules. Using multiple approaches, we found signatures of strong purifying selection on the KIR centromeric region, which codes for the strongest NK cell educator receptors, possibly driven by the limited HLA diversity in these populations. Our study expands the current knowledge of KIR genetic diversity in populations to understand KIR–HLA coevolution and its impact on human health and survival.     

TagSNP approach for HLA risk allele genotyping of Saudi celiac disease patients: effectiveness and pitfalls

Background: Celiac disease (CD) is a genetically complex autoimmune disease which is triggered by dietary gluten. Human leukocyte antigen (HLA) class II genes are known to act as high-risk markers for CD, where >95% of CD patients carry (HLA), DQ2 and/or DQ8 alleles. Therefore, the present study was conducted to investigate the distribution of HLA haplotypes among Saudi CD patients and healthy controls by using the tag single nucleotide polymorphisms (SNP).Methods: HLA-tag SNPs showing strong linkage value (r²>0.99) were used to predict the HLA DQ2 and DQ8 genotypes in 101 Saudi CD patients and in 103 healthy controls by using real-time polymerase chain reaction technique. Genotype calls were further validated by Sanger sequencing method.Results: A total of 63.7% of CD cases and of 60.2% of controls were predicted to carry HLA-DQ2 and DQ8 heterodimers, either in the homozygous or heterozygous states. The prevalence of DQ8 in our CD patients was predicted to be higher than the patients from other ethnic populations (35.6%). More than 32% of the CD patients were found to be non-carriers of HLA risk haplotypes as predicted by the tag SNPs.Conclusion: The present study highlights that the Caucasian specific HLA-tag SNPs would be of limited value to accurately predict CD specific HLA haplotypes in Saudi population, when compared with the Caucasian groups. Prediction of risk haplotypes by tag SNPs in ethnic groups is a good alternate approach as long as the tag SNPs were identified from the local population genetic variant databases.     

Multi-Sample Pooling and Illumina Genome Analyzer Sequencing Methods to Determine Gene Sequence Variation for Database Development

Determination of sequence variation within a genetic locus to develop clinically relevant databases is critical for molecular assay design and clinical test interpretation, so multisample pooling for Illumina genome analyzer (GA) sequencing was investigated using the RET proto-oncogene as a model. Samples were Sanger-sequenced for RET exons 10, 11, and 13–16. Ten samples with 13 known unique variants (“singleton variants” within the pool) and seven common changes were amplified and then equimolar-pooled before sequencing on a single flow cell lane, generating 36 base reads. For comparison, a single “control” sample was run in a different lane. After alignment, a 24-base quality score-screening threshold and 3` read end trimming of three bases yielded low background error rates with a 27% decrease in aligned read coverage. Sequencing data were evaluated using an established variant detection method (percent variant reads), by the presented subtractive correction method, and with SNPSeeker software. In total, 41 variants (of which 23 were singleton variants) were detected in the 10 pool data, which included all Sanger-identified variants. The 23 singleton variants were detected near the expected 5% allele frequency (average 5.17%±0.90% variant reads), well above the highest background error (1.25%). Based on background error rates, read coverage, simulated 30, 40, and 50 sample pool data, expected singleton allele frequencies within pools, and variant detection methods; ≥30 samples (which demonstrated a minimum 1% variant reads for singletons) could be pooled to reliably detect singleton variants by GA sequencing.     

Mapping Accuracy of Short Reads from Massively Parallel Sequencing and the Implications for Quantitative Expression Profiling

Background

Massively parallel sequencing offers an enormous potential for expression profiling, in particular for interspecific comparisons. Currently, different platforms for massively parallel sequencing are available, which differ in read length and sequencing costs. The 454-technology offers the highest read length. The other sequencing technologies are more cost effective, on the expense of shorter reads. Reliable expression profiling by massively parallel sequencing depends crucially on the accuracy to which the reads could be mapped to the corresponding genes.

Methodology/Principal Findings

We performed an in silico analysis to evaluate whether incorrect mapping of the sequence reads results in a biased expression pattern. A comparison of six available mapping software tools indicated a considerable heterogeneity in mapping speed and accuracy. Independently of the software used to map the reads, we found that for compact genomes both short (35 bp, 50 bp) and long sequence reads (100 bp) result in an almost unbiased expression pattern. In contrast, for species with a larger genome containing more gene families and repetitive DNA, shorter reads (35–50 bp) produced a considerable bias in gene expression. In humans, about 10% of the genes had fewer than 50% of the sequence reads correctly mapped. Sequence polymorphism up to 9% had almost no effect on the mapping accuracy of 100 bp reads. For 35 bp reads up to 3% sequence divergence did not affect the mapping accuracy strongly. The effect of indels on the mapping efficiency strongly depends on the mapping software.

Conclusions/Significance

In complex genomes, expression profiling by massively parallel sequencing could introduce a considerable bias due to incorrectly mapped sequence reads if the read length is short. Nevertheless, this bias could be accounted for if the genomic sequence is known. Furthermore, sequence polymorphisms and indels also affect the mapping accuracy and may cause a biased gene expression measurement. The choice of the mapping software is highly critical and the reliability depends on the presence/absence of indels and the divergence between reads and the reference genome. Overall, we found SSAHA2 and CLC to produce the most reliable mapping results.     

Targeted de novo phasing and long-range assembly by template mutagenesis

Short-read sequencers provide highly accurate reads at very low cost. Unfortunately, short reads are often inadequate for important applications such as assembly in complex regions or phasing across distant heterozygous sites. In this study, we describe novel bench protocols and algorithms to obtain haplotype-phased sequence assemblies with ultra-low error for regions 10 kb and longer using short reads only. We accomplish this by imprinting each template strand from a target region with a dense and unique mutation pattern. The mutation process randomly and independently converts ∼50% of cytosines to uracils. Sequencing libraries are made from both mutated and unmutated templates. Using de Bruijn graphs and paired-end read information, we assemble each mutated template and use the unmutated library to correct the mutated bases. Templates are partitioned into two or more haplotypes, and the final haplotypes are assembled and corrected for residual template mutations and PCR errors. With sufficient template coverage, the final assemblies have per-base error rates below 10^–9. We demonstrate this method on a four-member nuclear family, correctly assembling and phasing three genomic intervals, including the highly polymorphic HLA-B gene.     

Analysis of HLA class II haplotypes in the Cayapa Indians of Ecuador: a novel DRB1 allele reveals evidence for convergent evolution and balancing selection at position 86.

PCR amplification, oligonucleotide probe typing, and sequencing were used to analyze the HLA class II loci (DRB1, DQA1, DQB1, and DPB1) of an isolated South Amerindian tribe. Here we report HLA class II variation, including the identification of a new DRB1 allele, several novel DR/DQ haplotypes, and an unusual distribution of DPB1 alleles, among the Cayapa Indians (N = 100) of Ecuador. A general reduction of HLA class II allelic variation in the Cayapa is consistent with a population bottle-neck during the colonization of the Americas. The new Cayapa DRB1 allele, DRB1*08042, which arose by a G-->T point mutation in the parental DRB1*0802, contains a novel Val codon (GTT) at position 86. The generation of DRB1*08042 (Val-86) from DRB1*0802 (Gly-86) in the Cayapa, by a different mechanism than the (GT-->TG) change in the creation of DRB1*08041 (Val-86) from DRB1*0802 in Africa, implicates selection in the convergent evolution of position 86 DR beta variants. The DRB1*08042 allele has not been found in > 1,800 Amerindian haplotypes and thus presumably arose after the Cayapa separated from other South American Amerindians. Selection pressure for increased haplotype diversity can be inferred in the generation and maintenance of three new DRB1*08042 haplotypes and several novel DR/DQ haplotypes in this population. The DPB1 allelic distribution in the Cayapa is also extraordinary, with two alleles, DPB1*1401, a very rare allele in North American Amerindian populations, and DPB1*0402, the most common Amerindian DPB1 allele, constituting 89% of the Cayapa DPB1.(ABSTRACT TRUNCATED AT 250 WORDS)     

Detection of novel sequence heterogeneity and haplotypic diversity of HLA class II genes

Nucleic acid sequences of the second exons of HLA-DRB1, –DRB3/4/5, –DQB1, and –DQA1 genes were determined from 43 homozygous cell lines, representing each of the known class II haplotypes, and from 30 unrelated Caucasian subjects, comprising 60 haplotypes. This systematic sequence analysis was undertaken in order to a) determine the existence of sequence microheterogeneity among cell lines which type as identical by methods other than sequencing; b) determine whether direct sequencing of class II genes will identify the presence of more extensive sequence polymorphism at the population level than that identified with other typing methods; c) accurately determine the molecular composition of the known class II haplotypes; and d) study their evolutionary relatedness by maximum parsimony analysis. The identification of seven previously unidentified haplotypes carrying five new allelic amino acid sequences suggests that sequence microheterogeneity at the population level may be more frequent than previously thought. Maximum parsimony analysis of these haplotypes allowed their evolutionary classification and indicates that the higher mutation rate at DRB1 compared to DQB1 loci in most haplotypic groups is inversed in specific haplotype lineages. Furthermore, the extent and localization of gene conversions and point mutations at class II loci in the evolution of these haplotypes is significantly different at each locus. Identification of additional HLA class II molecular microheterogeneity suggests that direct sequence analysis of class II HLA genes can uncover new allelic sequences in the population and may represent a useful alternative to current typing methodologies to study the effects of sequence allelism in organ transplantation.The nucleotide sequence data reported in this paper have been submitted to the GenBank nucleotide sequence database and have been assigned the accession numbers M35890 through M35953.     

Regulation of HLA class I expression by non-coding gene variations

The Human Leukocyte Antigen (HLA) is a critical genetic system for different outcomes after solid organ and hematopoietic cell transplantation. Its polymorphism is usually determined by molecular technologies at the DNA level. A potential role of HLA allelic expression remains under investigation in the context of the allogenic immune response between donors and recipients. In this study, we quantified the allelic expression of all three HLA class I loci (HLA-A, B and C) by RNA sequencing and conducted an analysis of expression quantitative traits loci (eQTL) to investigate whether HLA expression regulation could be associated with non-coding gene variations. HLA-B alleles exhibited the highest expression levels followed by HLA-C and HLA-A alleles. The max fold expression variation was observed for HLA-C alleles. The expression of HLA class I loci of distinct individuals demonstrated a coordinated and paired expression of both alleles of the same locus. Expression of conserved HLA-A~B~C haplotypes differed in distinct PBMC’s suggesting an individual regulated expression of both HLA class I alleles and haplotypes. Cytokines TNFα /IFNβ, which induced a very similar upregulation of HLA class I RNA and cell surface expression across alleles did not modify the individually coordinated expression at the three HLA class I loci. By identifying cis eQTLs for the HLA class I genes, we show that the non-coding eQTLs explain 29%, 13%, and 31% of the respective HLA-A, B, C expression variance in unstimulated cells, and 9%, 23%, and 50% of the variance in cytokine-stimulated cells. The eQTLs have significantly higher effect sizes in stimulated cells compared to unstimulated cells for HLA-B and HLA-C genes expression. Our data also suggest that the identified eQTLs are independent from the coding variation which defines HLA alleles and thus may be influential on intra-allele expression variability although they might not represent the causal eQTLs.     

Fosmid-based whole genome haplotyping of a HapMap trio child: evaluation of Single Individual Haplotyping techniques

Determining the underlying haplotypes of individual human genomes is an essential, but currently difficult, step toward a complete understanding of genome function. Fosmid pool-based next-generation sequencing allows genome-wide generation of 40-kb haploid DNA segments, which can be phased into contiguous molecular haplotypes computationally by Single Individual Haplotyping (SIH). Many SIH algorithms have been proposed, but the accuracy of such methods has been difficult to assess due to the lack of real benchmark data. To address this problem, we generated whole genome fosmid sequence data from a HapMap trio child, NA12878, for which reliable haplotypes have already been produced. We assembled haplotypes using eight algorithms for SIH and carried out direct comparisons of their accuracy, completeness and efficiency. Our comparisons indicate that fosmid-based haplotyping can deliver highly accurate results even at low coverage and that our SIH algorithm, ReFHap, is able to efficiently produce high-quality haplotypes. We expanded the haplotypes for NA12878 by combining the current haplotypes with our fosmid-based haplotypes, producing near-to-complete new gold-standard haplotypes containing almost 98% of heterozygous SNPs. This improvement includes notable fractions of disease-related and GWA SNPs. Integrated with other molecular biological data sets, this phase information will advance the emerging field of diploid genomics.     

Viral Population Estimation Using Pyrosequencing

The diversity of virus populations within single infected hosts presents a major difficulty for the natural immune response as well as for vaccine design and antiviral drug therapy. Recently developed pyrophosphate-based sequencing technologies (pyrosequencing) can be used for quantifying this diversity by ultra-deep sequencing of virus samples. We present computational methods for the analysis of such sequence data and apply these techniques to pyrosequencing data obtained from HIV populations within patients harboring drug-resistant virus strains. Our main result is the estimation of the population structure of the sample from the pyrosequencing reads. This inference is based on a statistical approach to error correction, followed by a combinatorial algorithm for constructing a minimal set of haplotypes that explain the data. Using this set of explaining haplotypes, we apply a statistical model to infer the frequencies of the haplotypes in the population via an expectation–maximization (EM) algorithm. We demonstrate that pyrosequencing reads allow for effective population reconstruction by extensive simulations and by comparison to 165 sequences obtained directly from clonal sequencing of four independent, diverse HIV populations. Thus, pyrosequencing can be used for cost-effective estimation of the structure of virus populations, promising new insights into viral evolutionary dynamics and disease control strategies.     

An analysis of the feasibility of short read sequencing

Several methods for ultra high-throughput DNA sequencing are currently under investigation. Many of these methods yield very short blocks of sequence information (reads). Here we report on an analysis showing the level of genome sequencing possible as a function of read length. It is shown that re-sequencing and de novo sequencing of the majority of a bacterial genome is possible with read lengths of 20–30 nt, and that reads of 50 nt can provide reconstructed contigs (a contiguous fragment of sequence data) of 1000 nt and greater that cover 80% of human chromosome 1.     

An Integrated Tool to Study MHC Region: Accurate SNV Detection and HLA Genes Typing in Human MHC Region Using Targeted High-Throughput Sequencing

The major histocompatibility complex (MHC) is one of the most variable and gene-dense regions of the human genome. Most studies of the MHC, and associated regions, focus on minor variants and HLA typing, many of which have been demonstrated to be associated with human disease susceptibility and metabolic pathways. However, the detection of variants in the MHC region, and diagnostic HLA typing, still lacks a coherent, standardized, cost effective and high coverage protocol of clinical quality and reliability. In this paper, we presented such a method for the accurate detection of minor variants and HLA types in the human MHC region, using high-throughput, high-coverage sequencing of target regions. A probe set was designed to template upon the 8 annotated human MHC haplotypes, and to encompass the 5 megabases (Mb) of the extended MHC region. We deployed our probes upon three, genetically diverse human samples for probe set evaluation, and sequencing data show that ∼97% of the MHC region, and over 99% of the genes in MHC region, are covered with sufficient depth and good evenness. 98% of genotypes called by this capture sequencing prove consistent with established HapMap genotypes. We have concurrently developed a one-step pipeline for calling any HLA type referenced in the IMGT/HLA database from this target capture sequencing data, which shows over 96% typing accuracy when deployed at 4 digital resolution. This cost-effective and highly accurate approach for variant detection and HLA typing in the MHC region may lend further insight into immune-mediated diseases studies, and may find clinical utility in transplantation medicine research. This one-step pipeline is released for general evaluation and use by the scientific community.     

Association between HLA Variations and Chronic Hepatitis B Virus Infection in Saudi Arabian Patients

Hepatitis B virus (HBV) infection is a leading cause of liver diseases including cirrhosis and hepatocellular carcinoma. Human leukocyte antigens (HLAs) play an important role in the regulation of immune response against infectious organisms, including HBV. Recently, several genome-wide association (GWAS) studies have shown that genetic variations in HLA genes influence disease progression in HBV infection. The aim of this study was to investigate the role of HLA genetic polymorphisms and their possible role in HBV infection in Saudi Arabian patients. Variations in HLA genes were screened in 1672 subjects who were divided according to their clinical status into six categories as follows; clearance group, inactive carriers, active carriers, cirrhosis, hepatocellular carcinoma (HCC) patients and uninfected healthy controls. Three single nucleotide polymorphisms (SNPs) belonged to HLA-DQ region (rs2856718, rs7453920 and rs9275572) and two SNPs belonged to HLA-DP (rs3077 and rs9277535) were studied. The SNPs were genotyped by PCR-based DNA sequencing (rs2856718) and allele specific TaqMan genotyping assays (rs3077, rs7453920, rs9277535 and rs9275572). The results showed that rs2856718, rs3077, rs9277535 and rs9275572 were associated with HBV infection (p = 0.0003, OR = 1.351, CI = 1.147–1.591; p = 0.041, OR = 1.20, CI = 1.007–1.43; p = 0.045, OR = 1.198, CI = 1.004–1.43 and p = 0.0018, OR = 0.776, CI = 0.662–0.910, respectively). However, allele frequency of rs2856718, rs7453920 and rs9275572 were found more in chronically infected patients when compared to clearance group infection (p = 0.0001, OR = 1.462, CI = 1.204–1.776; p = 0.0178, OR = 1.267, CI = 1.042–1.540 and p = 0.010, OR = 0.776, CI = 0.639–0.942, respectively). No association was found when polymorphisms in HLA genes were compared in active carriers versus cirrhosis/HCC patients. In conclusion, these results suggest that variations in HLA genes could affect susceptibility to and clearance of HBV infection in Saudi Arabian patients.     

Rapid Short-Read Sequencing and Aneuploidy Detection Using MinION Nanopore Technology

MinION is a memory stick–sized nanopore-based sequencer designed primarily for single-molecule sequencing of long DNA fragments (>6 kb). We developed a library preparation and data-analysis method to enable rapid real-time sequencing of short DNA fragments (<1 kb) that resulted in the sequencing of 500 reads in 3 min and 40,000–80,000 reads in 2–4 hr at a rate of 30 nt/sec. We then demonstrated the clinical applicability of this approach by performing successful aneuploidy detection in prenatal and miscarriage samples with sequencing in <4 hr. This method broadens the application of nanopore-based single-molecule sequencing and makes it a promising and versatile tool for rapid clinical and research applications.     

Accurate assembly of minority viral haplotypes from next-generation sequencing through efficient noise reduction

Rapidly evolving RNA viruses continuously produce minority haplotypes that can become dominant if they are drug-resistant or can better evade the immune system. Therefore, early detection and identification of minority viral haplotypes may help to promptly adjust the patient’s treatment plan preventing potential disease complications. Minority haplotypes can be identified using next-generation sequencing, but sequencing noise hinders accurate identification. The elimination of sequencing noise is a non-trivial task that still remains open. Here we propose CliqueSNV based on extracting pairs of statistically linked mutations from noisy reads. This effectively reduces sequencing noise and enables identifying minority haplotypes with the frequency below the sequencing error rate. We comparatively assess the performance of CliqueSNV using an in vitro mixture of nine haplotypes that were derived from the mutation profile of an existing HIV patient. We show that CliqueSNV can accurately assemble viral haplotypes with frequencies as low as 0.1% and maintains consistent performance across short and long bases sequencing platforms.     

Molecular Dynamics Simulation Reveals the Selective Binding of Human Leukocyte Antigen Alleles Associated with Beh?et's Disease

Behçet’s disease (BD), a multi-organ inflammatory disorder, is associated with the presence of the human leukocyte antigen (HLA) HLA-B*51 allele in many ethnic groups. The possible antigen involvement of the major histocompatibility complex class I chain related gene A transmembrane (MICA-TM) nonapeptide (AAAAAIFVI) has been reported in BD symptomatic patients. This peptide has also been detected in HLA-A*26:01 positive patients. To investigate the link of BD with these two specific HLA alleles, molecular dynamics (MD) simulations were applied on the MICA-TM nonapeptide binding to the two BD-associated HLA alleles in comparison with the two non-BD-associated HLA alleles (B*35:01 and A*11:01). The MD simulations were applied on the four HLA/MICA-TM peptide complexes in aqueous solution. As a result, stabilization for the incoming MICA-TM was found to be predominantly contributed from van der Waals interactions. The P2/P3 residue close to the N-terminal and the P9 residue at the C-terminal of the MICA-TM nonapeptide served as the anchor for the peptide accommodated at the binding groove of the BD associated HLAs. The MM/PBSA free energy calculation predicted a stronger binding of the HLA/peptide complexes for the BD-associated HLA alleles than for the non-BD-associated ones, with a ranked binding strength of B*51:01 > B*35:01 and A*26:01 > A*11:01. Thus, the HLAs associated with BD pathogenesis expose the binding efficiency with the MICA-TM nonapeptide tighter than the non-associated HLA alleles. In addition, the residues 70, 73, 99, 146, 147 and 159 of the two BD-associated HLAs provided the conserved interaction for the MICA-TM peptide binding.     

Individual haplotyping of whale sharks from seawater environmental DNA

Population genetic data can provide valuable information on the demography of a species. For rare and elusive marine megafauna, samples for generating the data are traditionally obtained from tissue biopsies, which can be logistically difficult and expensive to collect and require invasive sampling techniques. Analysis of environmental DNA (eDNA) offers an alternative, minimally invasive approach to provide important genetic information. Although eDNA approaches have been studied extensively for species detection and biodiversity monitoring in metabarcoding studies, the potential for the technique to address population-level questions remains largely unexplored. Here, we applied “eDNA haplotyping” to obtain estimates of the intraspecific genetic diversity of a whale shark (Rhincodon typus) aggregation at Ningaloo reef, Australia. Over 2 weeks, we collected seawater samples directly behind individual sharks prior to taking a tissue biopsy sample from the same animal. Our data showed a 100% match between mtDNA sequences recovered in the eDNA and tissue sample for all 28 individuals sampled. In the seawater samples, >97% of all reads were assigned to six dominant haplotypes, and a clear dominant signal (~99% of sample reads) was recovered in each sample. Our study demonstrates accurate individual-level haplotyping from seawater eDNA. When DNA from one individual clearly dominates each eDNA sample, it provides many of the same opportunities for population genetic analyses as a tissue sample, potentially removing the need for tissue sampling. Our results show that eDNA approaches for population-level analyses have the potential to supply critical demographic data for the conservation and management of marine megafauna.