Kloosterman, W. | bioRxiv Science

bioRxiv2018

No evidence that mate choice in humans is dependent on the MHC

A long-standing hypothesis in biology proposes that various species select mates with a major histocompatibility complex (MHC) composition divergent from their own, so as to improve immune response in offspring. However, human and animal studies investigating this mate selection hypothesis have returned inconsistent results. Here, we analyze 239 mate-pairs of Dutch ancestry, all with whole-genome sequence data collected by the Genome of the Netherlands project, to investigate whether mate selection in humans is MHC dependent. We find no evidence for MHC-mediated mate selection in this sample (with an average MHC genetic similarity in mate pairs (Qc) = 0.829; permutation-based p = 0.703). Limiting the analysis to only common variation or considering the extended MHC region does not change our findings (Qc = 0.671, p = 0.513; and Qc = 0.844, p = 0.696, respectively). We demonstrate that the MHC in mate-pairs is no more genetically dissimilar (on average) than a pair of two randomly selected individuals, and conclude that there is no evidence to suggest that mate choice is influenced by genetic variation in the MHC.\n\nAuthor summaryStudies within various animal species have shown that the genetic content of the major histocompatibility complex (MHC) can influence mate choice. Such mate selection would be advantageous, as mating between individuals with different alleles across MHC genes would produce offspring with a more diverse MHC and therefore possess improved immune response to various pathogens. Studies of the influence on the MHC in human mate selection have been far less conclusive. Two studies of MHC-dependent mate selection performed on SNP data collected as part of the HapMap Consortium returned conflicting results: the first study reported significantly different MHC variation between mate pairs, and the second report refuted this claim. Here, we analyze a dataset comprised of 239 whole-genome sequenced Dutch mate pairs, a sample set an order of magnitude larger than the HapMap data and containing denser characterization of genetic variation. We find no evidence that the MHC influences mate selection in our population, and we show that this finding is robust to potential confounding factors and the types and frequencies of genetic variants analysed.

genetics↗

bioRxiv2017

Locus-Specific Enhancer Hubs And Architectural Loop Collisions Uncovered From Single Allele DNA Topologies

Chromatin folding is increasingly recognized as a regulator of genomic processes such as gene activity. Chromosome conformation capture (3C) methods have been developed to unravel genome topology through the analysis of pair-wise chromatin contacts and have identified many genes and regulatory sequences that, in populations of cells, are engaged in multiple DNA interactions. However, pair-wise methods cannot discern whether contacts occur simultaneously or in competition on the individual chromosome. We present a novel 3C method, Multi-Contact 4C (MC-4C), that applies Nanopore sequencing to study multi-way DNA conformations of tens of thousands individual alleles for distinction between cooperative, random and competing interactions. MC-4C can uncover previously missed structures in sub-populations of cells. It reveals unanticipated cooperative clustering between regulatory chromatin loops, anchored by enhancers and gene promoters, and CTCF and cohesin-bound architectural loops. For example, we show that the constituents of the active b-globin super-enhancer cooperatively form an enhancer hub that can host two genes at a time. We also find cooperative interactions between further dispersed regulatory sequences of the active proto-cadherin locus. When applied to CTCF-bound domain boundaries, we find evidence that chromatin loops can collide, a process that is negatively regulated by the cohesin release factor WAPL. Loop collision is further pronounced in WAPL knockout cells, suggestive of a \"cohesin traffic jam\". In summary, single molecule multi-contact analysis methods can reveal how the myriad of regulatory sequences spatially coordinate their actions on individual chromosomes. Insight into these single allele higher-order topological features will facilitate interpreting the consequences of natural and induced genetic variation and help uncovering the mechanisms shaping our genome.

genetics↗