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The new generation of massively parallel DNA sequencers, combined with the challenge of whole human genome resequencing, result in the need for rapid and accurate alignment of billions of short DNA sequence reads to a large reference genome. Speed is obviously of great importance, but equally important is maintaining alignment accuracy of short reads, in the 25-100 base range, in the presence of errors and true biological variation. We introduce a new algorithm specifically optimized for this task, as well as a freely available implementation, BFAST, which can align data produced by any of current sequencing platforms, allows for user-customizable levels of speed and accuracy, supports paired end data, and provides for efficient parallel and multi-threaded computation on a computer cluster. The new method is based on creating flexible, efficient whole genome indexes to rapidly map reads to candidate alignment locations, with arbitrary multiple independent indexes allowed to achieve robustness against read errors and sequence variants. The final local alignment uses a Smith-Waterman method, with gaps to support the detection of small indels. We compare BFAST to a selection of large-scale alignment tools -- BLAT, MAQ, SHRiMP, and SOAP -- in terms of both speed and accuracy, using simulated and real-world datasets. We show BFAST can achieve substantially greater sensitivity of alignment in the context of errors and true variants, especially insertions and deletions, and minimize false mappings, while maintaining adequate speed compared to other current methods. We show BFAST can align the amount of data needed to fully resequence a human genome, one billion reads, with high sensitivity and accuracy, on a modest computer cluster in less than 24 hours. BFAST is available at (http://bfast.sourceforge.net).

We use high-density single nucleotide polymorphism (SNP) genotyping microarrays to demonstrate the ability to accurately and robustly determine whether individuals are in a complex genomic DNA mixture. We first develop a theoretical framework for detecting an individual's presence within a mixture, then show, through simulations, the limits associated with our method, and finally demonstrate experimentally the identification of the presence of genomic DNA of specific individuals within a series of highly complex genomic mixtures, including mixtures where an individual contributes less than 0.1% of the total genomic DNA. These findings shift the perceived utility of SNPs for identifying individual trace contributors within a forensics mixture, and suggest future research efforts into assessing the viability of previously sub-optimal DNA sources due to sample contamination. These findings also suggest that composite statistics across cohorts, such as allele frequency or genotype counts, do not mask identity within genome-wide association studies. The implications of these findings are discussed.

Human pluripotent stem cells (hPSCs) can be directed to differentiate into skeletal muscle progenitor cells (SMPCs). However, the myogenicity of hPSC-SMPCs relative to human fetal or adult satellite cells remains unclear. We observed that hPSC-SMPCs derived by directed differentiation are less functional in vitro and in vivo compared to human satellite cells. Using RNA sequencing, we found that the cell surface receptors ERBB3 and NGFR demarcate myogenic populations, including PAX7 progenitors in human fetal development and hPSC-SMPCs. We demonstrated that hPSC skeletal muscle is immature, but inhibition of transforming growth factor-β signalling during differentiation improved fusion efficiency, ultrastructural organization and the expression of adult myosins. This enrichment and maturation strategy restored dystrophin in hundreds of dystrophin-deficient myofibres after engraftment of CRISPR–Cas9-corrected Duchenne muscular dystrophy human induced pluripotent stem cell-SMPCs. The work provides an in-depth characterization of human myogenesis, and identifies candidates that improve the in vivo myogenic potential of hPSC-SMPCs to levels that are equal to directly isolated human fetal muscle cells. Hicks et al. compare human pluripotent stem cell (hPSC)-derived muscle progenitors to fetal muscle cells, identify ERBB3/NGFR + populations with improved myogenic potential in vivo and enhance cell maturation by inhibiting TGF-β signalling during directed differentiation.

Intratumoral heterogeneity contributes to cancer drug resistance, but the underlying mechanisms are not understood. Single-cell analyses of patient-derived models and clinical samples from glioblastoma patients treated with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) demonstrate that tumor cells reversibly up-regulate or suppress mutant EGFR expression, conferring distinct cellular phenotypes to reach an optimal equilibrium for growth. Resistance to EGFR TKIs is shown to occur by elimination of mutant EGFR from extrachromosomal DNA. After drug withdrawal, reemergence of donai EGFR mutations on extrachromosomal DNA follows. These results indicate a highly specific, dynamic, and adaptive route by which cancers can evade therapies that target oncogenes maintained on extrachromosomal DNA.

U87MG is a commonly studied grade IV glioma cell line that has been analyzed in at least 1,700 publications over four decades. In order to comprehensively characterize the genome of this cell line and to serve as a model of broad cancer genome sequencing, we have generated greater than 30x genomic sequence coverage using a novel 50-base mate paired strategy with a 1.4kb mean insert library. A total of 1,014,984,286 mate-end and 120,691,623 single-end two-base encoded reads were generated from five slides. All data were aligned using a custom designed tool called BFAST, allowing optimal color space read alignment and accurate identification of DNA variants. The aligned sequence reads and mate-pair information identified 35 interchromosomal translocation events, 1,315 structural variations (>100 bp), 191,743 small (<21 bp) insertions and deletions (indels), and 2,384,470 single nucleotide variations (SNVs). Among these observations, the known homozygous mutation in PTEN was robustly identified, and genes involved in cell adhesion were overrepresented in the mutated gene list. Data were compared to 219,187 heterozygous single nucleotide polymorphisms assayed by Illumina 1M Duo genotyping array to assess accuracy: 93.83% of all SNPs were reliably detected at filtering thresholds that yield greater than 99.99% sequence accuracy. Protein coding sequences were disrupted predominantly in this cancer cell line due to small indels, large deletions, and translocations. In total, 512 genes were homozygously mutated, including 154 by SNVs, 178 by small indels, 145 by large microdeletions, and 35 by interchromosomal translocations to reveal a highly mutated cell line genome. Of the small homozygously mutated variants, 8 SNVs and 99 indels were novel events not present in dbSNP. These data demonstrate that routine generation of broad cancer genome sequence is possible outside of genome centers. The sequence analysis of U87MG provides an unparalleled level of mutational resolution compared to any cell line to date.

Mapping the methylome A newly developed method of characterizing an organism's 'methylome', that is the pattern of DNA methylation in the genome, has been used to generate a map of methylated cytosines in Arabidopsis to single base-pair resolution. The procedure, termed BS-Seq, combines bisulphite treatment of genomic DNA with ultra-high-throughput DNA sequencing to achieve a more precise and comprehensive result than previously possible. DNA methylation is an important factor in regulating gene expression, and this method, which can be applied to larger genomes like the mouse as well as to Arabidopsis , could prove a significant advance in the study of this form of gene regulation. In Arabidopsis , a map of methylated cytosines is generated at single base pair resolution by combining bisulphite treatment of genomic DNA with ultra-high-throughput sequencing. Cytosine DNA methylation is important in regulating gene expression and in silencing transposons and other repetitive sequences 1 , 2 . Recent genomic studies in Arabidopsis thaliana have revealed that many endogenous genes are methylated either within their promoters or within their transcribed regions, and that gene methylation is highly correlated with transcription levels 3 , 4 , 5 . However, plants have different types of methylation controlled by different genetic pathways, and detailed information on the methylation status of each cytosine in any given genome is lacking. To this end, we generated a map at single-base-pair resolution of methylated cytosines for Arabidopsis , by combining bisulphite treatment of genomic DNA with ultra-high-throughput sequencing using the Illumina 1G Genome Analyser and Solexa sequencing technology 6 . This approach, termed BS-Seq, unlike previous microarray-based methods, allows one to sensitively measure cytosine methylation on a genome-wide scale within specific sequence contexts. Here we describe methylation on previously inaccessible components of the genome and analyse the DNA methylation sequence composition and distribution. We also describe the effect of various DNA methylation mutants on genome-wide methylation patterns, and demonstrate that our newly developed library construction and computational methods can be applied to large genomes such as that of mouse.

Prenatal screening for Down syndrome has improved, but the number of resulting invasive diagnostic procedures remains problematic. Measurement of circulating cell-free DNA in maternal plasma might offer improvement. A blinded, nested case-control study was designed within a cohort of 4664 pregnancies at high risk for Down syndrome. Fetal karyotyping was compared with an internally validated, laboratory-developed test based on next-generation sequencing in 212 Down syndrome and 1484 matched euploid pregnancies. None had been previously tested. Primary testing occurred at a CLIA-certified commercial laboratory, with cross validation by a CLIA-certified university laboratory. Down syndrome detection rate was 98.6% (209/212), the false-positive rate was 0.20% (3/1471), and the testing failed in 13 pregnancies (0.8%); all were euploid. Before unblinding, the primary testing laboratory also reported multiple alternative interpretations. Adjusting chromosome 21 counts for guanine cytosine base content had the largest impact on improving performance. When applied to high-risk pregnancies, measuring maternal plasma DNA detects nearly all cases of Down syndrome at a very low false-positive rate. This method can substantially reduce the need for invasive diagnostic procedures and attendant procedure-related fetal losses. Although implementation issues need to be addressed, the evidence supports introducing this testing on a clinical basis.

Purpose: To determine whether maternal plasma cell–free DNA sequencing can effectively identify trisomy 18 and 13. Methods: Sixty-two pregnancies with trisomy 18 and 12 with trisomy 13 were selected from a cohort of 4,664 pregnancies along with matched euploid controls (including 212 additional Down syndrome and matched controls already reported), and their samples tested using a laboratory-developed, next-generation sequencing test. Interpretation of the results for chromosome 18 and 13 included adjustment for CG content bias. Results: Among the 99.1% of samples interpreted (1,971/1,988), observed trisomy 18 and 13 detection rates were 100% (59/59) and 91.7% (11/12) at false-positive rates of 0.28% and 0.97%, respectively. Among the 17 samples without an interpretation, three were trisomy 18. If z -score cutoffs for trisomy 18 and 13 were raised slightly, the overall false-positive rates for the three aneuploidies could be as low as 0.1% (2/1,688) at an overall detection rate of 98.9% (280/283) for common aneuploidies. An independent academic laboratory confirmed performance in a subset. Conclusion: Among high-risk pregnancies, sequencing circulating cell–free DNA detects nearly all cases of Down syndrome, trisomy 18, and trisomy 13, at a low false-positive rate. This can potentially reduce invasive diagnostic procedures and related fetal losses by 95%. Evidence supports clinical testing for these aneuploidies. Genet Med 2012:14(3):296–305

Oral-facial-digital (OFD) syndromes are a heterogeneous group of congenital disorders characterized by malformations of the face and oral cavity, and digit anomalies. Mutations within 12 cilia-related genes have been identified that cause several types of OFD, suggesting that OFDs constitute a subgroup of developmental ciliopathies. Through homozygosity mapping and exome sequencing of two families with variable OFD type 2, we identified distinct germline variants in INTS13 , a subunit of the Integrator complex. This multiprotein complex associates with RNA Polymerase II and cleaves nascent RNA to modulate gene expression. We determined that INTS13 utilizes its C-terminus to bind the Integrator cleavage module, which is disrupted by the identified germline variants p.S652L and p.K668Nfs*9. Depletion of INTS13 disrupts ciliogenesis in human cultured cells and causes dysregulation of a broad collection of ciliary genes. Accordingly, its knockdown in Xenopus embryos leads to motile cilia anomalies. Altogether, we show that mutations in INTS13 cause an autosomal recessive ciliopathy, which reveals key interactions between components of the Integrator complex. The integrator complex is required for the synthesis of protein coding and non-coding RNA and contains the protein INTS13. Here, the authors find germline mutations in INTS13 in two families with oral facial digital syndrome and show that the mutation affects the c-terminal domain of the protein and disrupts cilliogenesis.

Background Genetic ataxias are clinically heterogenous neurodegenerative conditions often involving rare or private mutations and it is often difficult to assign pathogenicity to rare gene variants solely based on DNA sequencing. An effective functional assay from an easy-to-obtain biospecimen would aid this assessment and be of high clinical value. SETX encodes a ubiquitous DNA/RNA helicase crucial for resolving R-loops and maintaining genome stability. Loss-of-function mutations cause a recessive disorder, Ataxia with Oculomotor Apraxia Type 2 (AOA2). Methods Here we utilize Weighted Gene Co-expression Network Analysis (WGCNA) from patient blood to construct an AOA2-specific transcriptomic signature as a biomarker to evaluate SETX variants in patients clinically suspected of having AOA2. Results WGCNA from peripheral blood RNA of 11 AOA2 patients from 7 families initially identified a single gene module that was modestly effective in distinguishing individuals with AOA2 from controls (sensitivity 73%, specificity 97%) and was able to robustly differentiate AOA2 patients from those with genetically distinct, yet phenotypically similar, neurological disorders (sensitivity 100%, specificity 100%). An independent derivation of the transcriptional biomarker identified a dual module model that was able to better distinguish individuals with AOA2 from controls (sensitivity 100%, specificity 97%). As validation, we examined a second cohort of 21 patients from 13 families and demonstrate that this dual module transcriptional biomarker could discriminate patients clinically suspected of AOA2 from controls (57%, 95%CI: 34%—78%). Overall, the transcriptional biomarker was able to separate AOA2 subjects ( n  = 32) from controls ( n  = 35) with 72% sensitivity and 97% specificity. Notably, this transcriptomic biomarker enabled verification of the first pathogenic SETX mutation found in a non-canonical transcript, expanding the spectrum of mutations that contribute to AOA2. Conclusions Our study identified a transcriptional biomarker that was able to differentiate AOA2 from controls and from other related neurological disorders, consequently expanding the spectrum of known pathogenic mutations. This proof-of-concept study illustrates that transcriptional biomarkers may be used to validate variants of uncertain significance in known genetic diseases.