We report the sequencing and assembly of a reference genome for the human GM12878 Utah/Ceph cell line using the MinION (Oxford Nanopore Technologies) nanopore sequencer. 91.2 Gb of sequence data, representing ~30× theoretical coverage, were produced. Reference-based alignment enabled detection of large structural variants and epigenetic modifications. De novo assembly of nanopore reads alone yielded a contiguous assembly (NG50 ~3 Mb). Next, we developed a protocol to generate ultra-long reads (N50 > 100kb, up to 882 kb). Incorporating an additional 5×-coverage of this data type more than doubled the assembly contiguity (NG50 ~6.4 Mb). The final assembled genome was 2,867 million bases in size, covering 85.8% of the reference. Assembly accuracy, after incorporating complementary short-read sequencing data, exceeded 99.8%. Ultra-long reads enabled assembly and phasing of the 4 Mb major histocompatibility complex (MHC) locus in its entirety, measurement of telomere repeat length and closure of gaps in the reference human genome assembly GRCh38.

We performed a genome-wide association study in non-Hispanic white subjects with fibrotic idiopathic interstitial pneumonias (N=1616) and controls (N=4683); replication was assessed in 876 cases and 1890 controls. We confirmed association with TERT and MUC5B on chromosomes 5p15 and 11p15, respectively, the chromosome 3q26 region near TERC, and identified 7 novel loci (PMeta = 2.4×10−8 to PMeta = 1.1×10−19). The novel loci include FAM13A (4q22), DSP (6p24), OBFC1 (10q24), ATP11A (13q34), DPP9 (19p13), and chromosomal regions 7q22 and 15q14-15. Our results demonstrate that genes involved in host defense, cell-cell adhesion, and DNA repair contribute to the risk of fibrotic IIP.

The biological interpretation of gene lists with interesting shared properties, such as up- or down-regulation in a particular experiment, is typically accomplished using gene ontology enrichment analysis tools. Given a list of genes, a gene ontology (GO) enrichment analysis may return hundreds of statistically significant GO results in a “flat” list, which can be challenging to summarize. It can also be difficult to keep pace with rapidly expanding biological knowledge, which often results in daily changes to any of the over 47,000 gene ontologies that describe biological knowledge. GOATOOLS, a Python-based library, makes it more efficient to stay current with the latest ontologies and annotations, perform gene ontology enrichment analyses to determine over- and under-represented terms, and organize results for greater clarity and easier interpretation using a novel GOATOOLS GO grouping method. We performed functional analyses on both stochastic simulation data and real data from a published RNA-seq study to compare the enrichment results from GOATOOLS to two other popular tools: DAVID and GOstats. GOATOOLS is freely available through GitHub: https://github.com/tanghaibao/goatools.

Summary Mosdepth is a new command-line tool for rapidly calculating genome-wide sequencing coverage. It measures depth from BAM or CRAM files at either each nucleotide position in a genome or for sets of genomic regions. Genomic regions may be specified as either a BED file to evaluate coverage across capture regions, or as a fixed-size window as required for copy-number calling. Mosdepth uses a simple algorithm that is computationally efficient and enables it to quickly produce coverage summaries. We demonstrate that mosdepth is faster than existing tools and provides flexibility in the types of coverage profiles produced.Availability and implementation mosdepth is available from https://github.com/brentp/mosdepth under the MIT license.Supplementary information Supplementary data are available at Bioinformatics online.