Physical interactions between genetic elements located throughout the genome play important roles in gene regulation and can be identified with the Chromosome Conformation Capture (3C) methodology. 3C converts physical chromatin interactions into specific ligation products, which are quantified individually by PCR. Here we present a high-throughput 3C approach, 3C-Carbon Copy (5C), that employs microarrays or quantitative DNA sequencing using 454-technology as detection methods. We applied 5C to analyze a 400-kb region containing the human ␤-globin locus and a 100-kb conserved gene desert region. We validated 5C by detection of several previously identified looping interactions in the ␤-globin locus. We also identified a new looping interaction in K562 cells between the ␤-globin Locus Control Region and the ␥-␦-globin intergenic region. Interestingly, this region has been implicated in the control of developmental globin gene switching. 5C should be widely applicable for large-scale mapping of cis-and trans-interaction networks of genomic elements and for the study of higher-order chromosome structure.

Chromatin has a complex spatial organization in the cell nucleus that serves vital functional purposes. A variety of chromatin folding conformations has been detected by single-cell imaging and chromosome conformation capture-based approaches. However, a unified quantitative framework describing spatial chromatin organization is still lacking. Here, we explore the "strings and binders switch" model to explain the origin and variety of chromatin behaviors that coexist and dynamically change within living cells. This simple polymer model recapitulates the scaling properties of chromatin folding reported experimentally in different cellular systems, the fractal state of chromatin, the processes of domain formation, and looping out. Additionally, the strings and binders switch model reproduces the recently proposed "fractal-globule" model, but only as one of many possible transient conformations.genome organization | genome architecture | long-range chromatin interactions | fluorescence in situ hybridization | Monte Carlo simulations U nderstanding the interplay between genome architecture and gene regulation is one of the most challenging problems in biology. During mitosis, chromosomes are found in a condensed state, but decondense during interphase, when highly coordinated cellular processes such as transcription, DNA repair, and replication take place, creating cell-type-specific chromatin folding (1-3).Chromosome organization occurs at different scales of genomic length to yield variable degrees of compaction (4). Linear nucleosome arrays fold into higher-order structures, first through local chromatin interactions, such as between promoters and enhancers, and then eventually giving rise to discrete chromosome territories (1).Spatial genome organization is guided by intra-and interchromosomal interactions mediated by nuclear components that include transcription factors, transcription and replication factories, Polycomb bodies, and contacts with the lamina (5-8). However, how binding of diffusible factors to specific genomic regions drives chromatin folding remains poorly understood.Imaging of single loci by FISH and genome-wide mapping of chromatin interactions by chromosome conformation capture (3C) approaches revealed a variety of chromatin architectures across genomic regions and cell types, and upon environmental cues (9-14) (Fig. S1A). In FISH experiments, chromatin folding is often measured by the mean-square spatial distance, R 2 ðsÞ, between two genomic regions as a function of their linear genomic distance, s (Fig. S1B), which usually exhibits scaling properties R 2 ðsÞ ∼ s 2v . Although the behavior of R 2 ðsÞ appears to depend on the genomic regions and cell types assessed (Fig. S1A), in general, at large genomic distances, R 2 ðsÞ reaches a plateau (i.e., v ¼ 0) that reflects the folding of chromosomes into territories (15).A global analysis of genome-wide 3C (Hi-C) ligation products in human cells averaged across all chromosomes has been used to estimate the "contact probability," P c ðsÞ (13). Th...

Gemin3 is a DEAD-box RNA helicase that binds to the Survival of Motor Neurons (SMN) protein and is a component of the SMN complex, which also comprises SMN, Gemin2, Gemin4, Gemin5, and Gemin6. Reduction in SMN protein results in Spinal muscular atrophy (SMA), a common neurodegenerative disease. The SMN complex has critical functions in the assembly/restructuring of diverse ribonucleoprotein (RNP) complexes. Here we report that Gemin3 and Gemin4 are also in a separate complex that contains eIF2C2, a member of the Argonaute protein family. This novel complex is a large approximately 15S RNP that contains numerous microRNAs (miRNAs). We describe 40 miRNAs, a few of which are identical to recently described human miRNAs, a class of small endogenous RNAs. The genomic sequences predict that miRNAs are likely to be derived from larger precursors that have the capacity to form stem-loop structures.

SummaryThe organization of the genome in the nucleus and the interactions of genes with their regulatory elements are key features of transcriptional control and their disruption can cause disease. We developed a novel genome-wide method, Genome Architecture Mapping (GAM), for measuring chromatin contacts, and other features of three-dimensional chromatin topology, based on sequencing DNA from a large collection of thin nuclear sections. We apply GAM to mouse embryonic stem cells and identify an enrichment for specific interactions between active genes and enhancers across very large genomic distances, using a mathematical model ‘SLICE’ (Statistical Inference of Co-segregation). GAM also reveals an abundance of three-way contacts genome-wide, especially between regions that are highly transcribed or contain super-enhancers, highlighting a previously inaccessible complexity in genome architecture and a major role for gene-expression specific contacts in organizing the genome in mammalian nuclei.

SUMMARY The extent to which low-frequency (minor allele frequency [MAF] between 1–5%) and rare (MAF ≤ 1%) variants contribute to complex traits and disease in the general population is largely unknown. Bone mineral density (BMD) is highly heritable, is a major predictor of osteoporotic fractures and has been previously associated with common genetic variants1–8, and rare, population-specific, coding variants9. Here we identify novel non-coding genetic variants with large effects on BMD (ntotal = 53,236) and fracture (ntotal = 508,253) in individuals of European ancestry from the general population. Associations for BMD were derived from whole-genome sequencing (n=2,882 from UK10K), whole-exome sequencing (n= 3,549), deep imputation of genotyped samples using a combined UK10K/1000Genomes reference panel (n=26,534), and de-novo replication genotyping (n= 20,271). We identified a low-frequency non-coding variant near a novel locus, EN1, with an effect size 4-fold larger than the mean of previously reported common variants for lumbar spine BMD8 (rs11692564[T], MAF = 1.7%, replication effect size = +0.20 standard deviations [SD], Pmeta = 2×10−14), which was also associated with a decreased risk of fracture (OR = 0.85; P = 2×10−11; ncases = 98,742 and ncontrols = 409,511). Using an En1Cre/flox mouse model, we observed that conditional loss of En1 results in low bone mass, likely as a consequence of high bone turn-over. We also identified a novel low-frequency non-coding variant with large effects on BMD near WNT16 (rs148771817[T], MAF = 1.1%, replication effect size = +0.39 SD, Pmeta = 1×10−11). In general, there was an excess of association signals arising from deleterious coding and conserved non-coding variants. These findings provide evidence that low-frequency non-coding variants have large effects on BMD and fracture, thereby providing rationale for whole-genome sequencing and improved imputation reference panels to study the genetic architecture of complex traits and disease in the general population.