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Genes in the major histocompatibility complex MHC, also known as HLA play a critical role in the immune response and variation within the extended 4-Mb region shows association with major risks of many diseases. Yet, deciphering the underlying causes of these associations ggi difficult because the MHC is the most polymorphic region of the genome with a complex linkage disequilibrium structure.

Here, we reconstruct full MHC haplotypes from de novo assembled trios without relying on a reference genome and perform evolutionary analyses.

We report full MHC haplotypes and call a large set of structural variants in the regions for future use in imputation with GWAS data. We also present the first complete analysis of the recombination landscape in the entire region and show how balancing selection at classical genes have linked effects bti the frequency of variants throughout the region. The major histocompatibility complex covers 4 Mb on Chromosome 6 and is the most polymorphic part of the human genome.

Most of approximately genes in the region are directly involved with the immune system. The high diversity is thought to be bi by balancing selection acting on several individual genes combined with an overall small recombination rate in the MHC DeGiorgio et al.

Genome-wide association studies have revealed the MHC to be the most important region in the human genome for disease associations, in particular for autoimmune diseases Trowsdale and Knight ; Zhou et al. The very high diversity and wide-ranging linkage disequilibrium LD makes it difficult to disentangle selective forces and to accurately pinpoint the variants responsible for disease associations.

Many regions are too variable for reliable identification of variants from mapping of short reads to the human reference genome. LD causes multiple nearby variants to provide the same statistical evidence of association hampering the identification of causal variants. In addition to the human genome reference MHC haplotype, seven other haplotypes have been sequenced Horton et al.

There is a strong need for obtaining a larger number of full MHC haplotypes, which requires de novo assembly of the haplotypes without the use of a reference genome. Long-read technology and refined capture methods are potentially very powerful Chaisson et al. The Danish Pan-Genome project Maretty et al. We use data from 25 of these trios to reconstruct and analyze the four 0521 MHC haplotypes in each trio haplotypes in total.

Our approach combines the de novo assemblies with transmission information, read-backed phasing, and joint analysis of each trio.

Here, we describe our method of assembly and phasing in detail and perform an evolutionary analysis of the resulting haplotypes. Our assembly approach was designed big circumvent the challenges in mapping short reads to a reference sequence. Through several steps, we leverage transmission information and read-backed phasing to create candidate haplotypes to which we can map reads. Because the candidate haplotypes were created from the reads themselves, subsequent mapping is more successful than mapping to the reference genome, and phasing is improved.

The procedure of mapping and phasing is iterated, as each inferred phased haplotype improves mapping and in turn phasing. Figure 1 shows a schematic of our pipeline. Assembly of full MHC haplotypes.

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Schematic showing the construction of MHC haplotypes. Scaffolds larger than 50 kb mapping to the MHC are extracted and concatenated, creating diploid consensus scaffolds step 2.

Bubbles in the alignment graphs for individuals in the trio are mapped big within the trio by exact matching of the sequence upstream of the bubbles step 3. Global alignment between phased bubbles is used bgk create a consensus sequence between transmitted parental and inherited child haplotype sequences steps bgo and 5. Reads from parents and child are then mapped to the consensus sequence, genotyped, and phased step 6gaps are closed step 7and reads are mapped again for another iteration of mapping, genotyping, and phasing step 8.

We extracted scaffolds mapping with at least 50 kb to the MHC region the number of scaffolds ranges from 1 to 8 across individuals Supplemental Fig.

S1a and concatenated these to create diploid consensus scaffolds including bubbles in the assembly graph step bggi. After phasing, we created a sequence for each nontransmitted parental haplotype and created a consensus sequence between transmitted parental haplotypes and inherited child haplotypes by multiple global alignments of segments between phased bubbles steps 4 and 5.

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We then mapped reads to the transmitted consensus haplotypes and genotyped and phased them using transmission information and 5201 phasing step 6.

We evaluated the accuracy of variant calling and phasing by cloning and Sanger sequencing of five clones from 75 random fragments from highly polymorphic regions containing between two and 10 variants variants in total. We used simulations to further evaluate the power and accuracy of our approach by simulating reads in an artificial trio with known MHC haplotypes, reconstructing the haplotypes using our pipeline, and comparing these to the original haplotypes.

We simulated reads from a trio with four of the different reference haplotypes—pgf and mcf in the mother, cox and qbl in the father, and bvi and cox in the child. Reads were simulated to exactly reflect the coverage, bbi size distribution, and error profile as our own sequencing.

De novo assembly and inference of phased haplotypes were then done in exactly the same way as for the real data using our pipeline outlined in Figure 1 ; we then investigated whether we could separately bgu the cox and the pgf haplotypes in the child.

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Supplemental Figure S2a and b, shows that although the initial assembly in the child is a mixture of the two haplotypes, the final haplotypes generally align 55021 the whole region with pgf and cox, respectively, showing that the pipeline has phased them.

We found that S2band the lengths of incorrectly phased segments were generally very short compared to big correctly phased segments Supplemental Fig. Because collapse of paralogous or repetitive sequence might be a likely error mode in the 50021 haplotypes Alkan et al. The six incomplete reference haplotypes all show a strong deficiency in these elements. The length of the individual haplotypes range from 4. S1dand missing data in the haplotypes range between 0.

It also shows that there are large blocks of missing data in six of the eight haplotypes supplied with the reference genome. To visualize the differences among our haplotypes, we aligned them one by one to the pgf and cox reference haplotypes from hg38 bi MAFFT Katoh and Standley and scored the percentage of differences in the alignment in kb windows along the MHC.

Figure 2 shows a bgj plot of differences with the pgf haplotype a similar heat plot against cox is found in Supplemental Fig. Differences between MHC haplotypes and reference pgf. The new haplotypes and the seven alternative reference haplotypes were aligned to the reference pgf haplotype through pairwise alignment, and the percentage of pairwise differences was calculated in bins of 10 kb, shown here in white low to red high.

The region classes and important genes such as the classical loci are shown above.

Assembly and analysis of full MHC haplotypes from the Danish population

C4A and C4B are marked in blue. The six existing haplotypes from the human reference genome are included for comparison, showing that these contain many sequencing gaps. In contrast, our new haplotypes contain fewer sequencing gaps Supplemental Fig. The diversity is variable but generally very high across the region.

In the proximal part of the class II region, diversity is so high that alignment becomes unreliable, explaining well why mapping-based approaches fail in this region, which is also among the most important in association mapping studies.

When we align to the cox haplotype, we can improve alignment in this region significantly for most haplotypes Supplemental Fig. S5 ; however, for some haplotypes, alignment is still poor. We conclude that identification of structural variation in this region by alignment to the reference haplotype is not reliable Dilthey et al. Because all of our new haplotypes come from the Danish population, which genetically is quite homogenous Athanasiadis et al.

To investigate this, we sampled five random diploid MHC regions from each of the 26 populations in The Genomes Project The Genomes Project Consortium and compared the sampled regions with our new haplotypes using principal component analysis and constructing a neighbor-joining tree based on the distance matrix computed from the data Supplemental Fig.

For population genetics analyses, we chose to focus on the haplotypes with the most phased variants and the least amount of sequence gaps—the 50 haplotypes transmitted to the children. To obtain a reliable variant call set in reference genome coordinates, we aligned against hg38 and used the AsmVar pipeline Liu et al.

From a candidate set ofSNV and 32, structural variants, we call and genotype 50, SNVs and indels and complex variants.

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In contrast, we only found a total of 16, variants in our initial analysis in which we used the unphased scaffolds in the MHC region for variant calling. In our samples, SNPs were polymorphic and genotyped in all individuals in our call set and on the chip. We found an overall concordance of Because of the complexity and inaccessibility of the MHC region, most previous studies have focused on specific regions of the MHC.

Our new haplotypes allowed us to gain a more global view of the region. The site frequency spectrum is shifted toward more common variants in the whole region and in the classical HLA genes in particular when compared to the rest of the genome. Nucleotide diversity is far above genome average in three broad regions, where the folded site frequency spectrum of SNVs is also shifted to intermediate frequencies.

Indels occur with higher relative frequency outside classical loci compared to SNVs and with higher minor allele frequencies also Fig. Variation and population genetics. We observe Tajima’s D statistics above genome-wide values extending from the classical loci along with an increase in the proportion of nonsynonymous variants, consistent with linkage to sites under balancing selection in classical MHC genes Fig.

The recombination rate inferred using LDhat Auton and McVean is highly variable across the entire MHC region, with recombination rate hotspots interspersed with regions of very low recombination rate Fig.

We find no strong overall correlation between gene density and recombination rate, but in the most gene dense part of the class III region, we find long sequence stretches with low recombination rate. We find a high recombination rate in classical loci but also observe a high recombination rate outside classical loci, especially upstream of the Class I region. Recombination across the MHC region. Recombination rate estimated across the MHC region.

Arrowheads point up toward two outliers that were removed for better visualization of the rest of the region. In order to study potential consequences on linked diversity of balancing selection acting in the MHC region, we first chose to focus on a region 60 kb upstream of and including the classical HLA-DRA gene Fig.

We detected strong LD extending upstream of the gene Fig. These observations are also reflected in the estimated recombination rate in the region Fig.

Although we see a minor peak in recombination rate between the genes, recombination rate is generally much lower compared to the entire region Fig. These observations suggest that balancing selection cause increased frequency of variation in genes linked to the classical HLA-DRA gene. A Average minor allele frequencies MAF across the region. B Tajima’s D statistic calculated in 1-kb bins. C Recombination rate estimate. We then decided to test whether this effect could be detected in other HLA genes known to be under balancing selection.

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In order to study the importance of selection and the frequency of coding variants in linked genes in general, we calculated the average minor allele frequency MAF of synonymous and nonsynonymous variants as a function of distance to the 0521 of nine HLA genes classical HLA loci previously shown to be bti balancing selection DeGiorgio et al. Variants within the classical MHC genes are not included. A linear regression was fitted for each variant type on the nonbinned data.

These results are in line with the findings of Lenz et al. As a control, we randomly selected nine genes from the MHC region and compared the same metric but found no significant correlation between MAF and distance to the nearest control gene for synonymous variants and, although significant for nonsynonymous variants, the slope was in the opposite direction, i.

As a control, we selected nine genes in the genome, chosen randomly, but matched in length with a classical HLA gene, so a control gene of similar length matched each classical HLA gene.

These observations suggest that linked selection keeps variants in other genes at higher frequency with potential detrimental effects if some of these variants have a direct effect on fitness. Our ability to assemble highly accurate full MHC haplotypes has allowed us to present a global view of the variation along this important region of the human genome.

The preponderance of new structural variation shows that de novo assembly is necessary in order to catalog the full variation in the region.