Diversity of KIR, HLA Class I, and Their Interactions in Seven Populations of Sub-Saharan Africans.

HLA class I and KIR sequences were determined for Dogon, Fulani, and Baka populations of western Africa, Mbuti of central Africa, and Datooga, Iraqw, and Hadza of eastern Africa. Study of 162 individuals identified 134 HLA class I alleles (41 HLA-A, 60 HLA-B, and 33 HLA-C). Common to all populations are three HLA-C alleles (C1+C*07:01, C1+C*07:02, and C2+C*06:02) but no HLA-A or -B Unexpectedly, no novel HLA class I was identified in these previously unstudied and anthropologically distinctive populations. In contrast, of 227 KIR detected, 22 are present in all seven populations and 28 are novel. A high diversity of HLA A-C-B haplotypes was observed. In six populations, most haplotypes are represented just once. But in the Hadza, a majority of haplotypes occur more than once, with 2 having high frequencies and 10 having intermediate frequencies. The centromeric (cen) part of the KIR locus exhibits an even balance between cenA and cenB in all seven populations. The telomeric (tel) part has an even balance of telA to telB in East Africa, but this changes across the continent to where telB is vestigial in West Africa. All four KIR ligands (A3/11, Bw4, C1, and C2) are present in six of the populations. HLA haplotypes of the Iraqw and Hadza encode two KIR ligands, whereas the other populations have an even balance between haplotypes encoding one and two KIR ligands. Individuals in these African populations have a mean of 6.8-8.4 different interactions between KIR and HLA class I, compared with 2.9-6.5 for non-Africans.

Highly scalable generation of DNA methylation profiles in single cells.

We present a highly scalable assay for whole-genome methylation profiling of single cells. We use our approach, single-cell combinatorial indexing for methylation analysis (sci-MET), to produce 3,282 single-cell bisulfite sequencing libraries and achieve read alignment rates of 68 ± 8%. We apply sci-MET to discriminate the cellular identity of a mixture of three human cell lines and to identify excitatory and inhibitory neuronal populations from mouse cortical tissue.

Haplotype phasing of whole human genomes using bead-based barcode partitioning in a single tube.

Haplotype-resolved genome sequencing promises to unlock a wealth of information in population and medical genetics. However, for the vast majority of genomes sequenced to date, haplotypes have not been determined because of cumbersome haplotyping workflows that require fractions of the genome to be sequenced in a large number of compartments. Here we demonstrate barcode partitioning of long DNA molecules in a single compartment using "on-bead" barcoded tagmentation. The key to the method that we call "contiguity preserving transposition" sequencing on beads (CPTv2-seq) is transposon-mediated transfer of homogenous populations of barcodes from beads to individual long DNA molecules that get fragmented at the same time (tagmentation). These are then processed to sequencing libraries wherein all sequencing reads originating from each long DNA molecule share a common barcode. Single-tube, bulk processing of long DNA molecules with ∼150,000 different barcoded bead types provides a barcode-linked read structure that reveals long-range molecular contiguity. This technology provides a simple, rapid, plate-scalable and automatable route to accurate, haplotype-resolved sequencing, and phasing of structural variants of the genome.

Sequences of 95 human MHC haplotypes reveal extreme coding variation in genes other than highly polymorphic HLA class I and II.

The most polymorphic part of the human genome, the MHC, encodes over 160 proteins of diverse function. Half of them, including the HLA class I and II genes, are directly involved in immune responses. Consequently, the MHC region strongly associates with numerous diseases and clinical therapies. Notoriously, the MHC region has been intractable to high-throughput analysis at complete sequence resolution, and current reference haplotypes are inadequate for large-scale studies. To address these challenges, we developed a method that specifically captures and sequences the 4.8-Mbp MHC region from genomic DNA. For 95 MHC homozygous cell lines we assembled, de novo, a set of high-fidelity contigs and a sequence scaffold, representing a mean 98% of the target region. Included are six alternative MHC reference sequences of the human genome that we completed and refined. Characterization of the sequence and structural diversity of the MHC region shows the approach accurately determines the sequences of the highly polymorphic HLA class I and HLA class II genes and the complex structural diversity of complement factor C4A/C4B It has also uncovered extensive and unexpected diversity in other MHC genes; an example is MUC22, which encodes a lung mucin and exhibits more coding sequence alleles than any HLA class I or II gene studied here. More than 60% of the coding sequence alleles analyzed were previously uncharacterized. We have created a substantial database of robust reference MHC haplotype sequences that will enable future population scale studies of this complicated and clinically important region of the human genome.

Defining KIR and HLA Class I Genotypes at Highest Resolution via High-Throughput Sequencing.

The physiological functions of natural killer (NK) cells in human immunity and reproduction depend upon diverse interactions between killer cell immunoglobulin-like receptors (KIRs) and their HLA class I ligands: HLA-A, HLA-B, and HLA-C. The genomic regions containing the KIR and HLA class I genes are unlinked, structurally complex, and highly polymorphic. They are also strongly associated with a wide spectrum of diseases, including infections, autoimmune disorders, cancers, and pregnancy disorders, as well as the efficacy of transplantation and other immunotherapies. To facilitate study of these extraordinary genes, we developed a method that captures, sequences, and analyzes the 13 KIR genes and HLA-A, HLA-B, and HLA-C from genomic DNA. We also devised a bioinformatics pipeline that attributes sequencing reads to specific KIR genes, determines copy number by read depth, and calls high-resolution genotypes for each KIR gene. We validated this method by using DNA from well-characterized cell lines, comparing it to established methods of HLA and KIR genotyping, and determining KIR genotypes from 1000 Genomes sequence data. This identified 116 previously uncharacterized KIR alleles, which were all demonstrated to be authentic by sequencing from source DNA via standard methods. Analysis of just two KIR genes showed that 22% of the 1000 Genomes individuals have a previously uncharacterized allele or a structural variant. The method we describe is suited to the large-scale analyses that are needed for characterizing human populations and defining the precise HLA and KIR factors associated with disease. The methods are applicable to other highly polymorphic genes.