From: My NCBI <email@example.com>
Date: Sat, Oct 1, 2011 at 6:50 PM
Subject: What's new for 'next generation sequencing' in PubMed
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|1.||The near demise and subsequent revival of classical genetics for investigating Caenorhabditis elegans embryogenesis: RNAi meets next-generation DNA sequencing.|
|Mol Biol Cell. 2011 Oct;22(19):3556-8.|
Molecular genetic investigation of the early Caenorhabditis elegans embryo has contributed substantially to the discovery and general understanding of the genes, pathways, and mechanisms that regulate and execute developmental and cell biological processes. Initially, worm geneticists relied exclusively on a classical genetics approach, isolating mutants with interesting phenotypes after mutagenesis and then determining the identity of the affected genes. Subsequently, the discovery of RNA interference (RNAi) led to a much greater reliance on a reverse genetics approach: reducing the function of known genes with RNAi and then observing the phenotypic consequences. Now the advent of next-generation DNA sequencing technologies and the ensuing ease and affordability of whole-genome sequencing are reviving the use of classical genetics to investigate early C. elegans embryogenesis.
|PMID: 21960050 [PubMed - in process]|
|2.||Challenges in studying genomic structural variant formation mechanisms: The short-read dilemma and beyond.|
|Onishi-Seebacher M, Korbel JO.|
|Bioessays. 2011 Sep 30. doi: 10.1002/bies.201100075. [Epub ahead of print]|
Next-generation sequencing (NGS) technologies have revolutionised the analysis of genomic structural variants (SVs), providing significant insights into SV de novo formation based on analyses of rearrangement breakpoint junctions. The short DNA reads generated by NGS, however, have also created novel obstacles by biasing the ascertainment of SVs, an aspect that we refer to as the 'short-read dilemma'. For example, recent studies have found that SVs are often complex, with SV formation generating large numbers of breakpoints in a single event (multi-breakpoint SVs) or structurally polymorphic loci having multiple allelic states (multi-allelic SVs). This complexity may be obscured in short reads, unless the data is analysed and interpreted within its wider genomic context. We discuss how novel approaches will help to overcome the short-read dilemma, and how integration of other sources of information, including the structure of chromatin, may help in the future to deepen the understanding of SV formation processes.
|PMID: 21959584 [PubMed - as supplied by publisher]|
|3.||Exome sequencing and subsequent association studies identify five amino acid-altering variants influencing human height.|
|Kim JJ, Park YM, Baik KH, Choi HY, Yang GS, Koh I, Hwang JA, Lee J, Lee YS, Rhee H, Kwon TS, Han BG, Heath KE, Inoue H, Yoo HW, Park K, Lee JK.|
|Hum Genet. 2011 Sep 29. [Epub ahead of print]|
Height is a highly heritable trait that involves multiple genetic loci. To identify causal variants that influence stature, we sequenced whole exomes of four children with idiopathic short stature. Ninety-five nonsynonymous single-nucleotide polymorphisms (nsSNPs) were selected as potential candidate variants. We performed association analysis in 740 cohort individuals and identified 11 nsSNPs in 10 loci (DIS3L2, ZBTB38, FAM154A, PTCH1, TSSC4, KIF18A, GPR133, ACAN, FAM59A, and NINL) associated with adult height (P < 0.05), including five novel loci. Of these, two nsSNPs (TSSC4 and KIF18A loci) were significant at P < 0.05 in the replication study (n = 1,000) and five (ZBTB38, FAM154A, TSSC4, KIF18A, and FAM59A loci) were significant at P < 0.01 in the combined analysis (n = 1,740). Together, the five nsSNPs accounted for approximately 2.5% of the height variation. This study demonstrated the utility of next-generation sequencing in identifying genetic variants and loci associated with complex traits.
|PMID: 21959382 [PubMed - as supplied by publisher]|
|4.||Single-molecule direct RNA sequencing without cDNA synthesis.|
|Ozsolak F, Milos PM.|
|Wiley Interdiscip Rev RNA. 2011 Jul;2(4):565-70. doi: 10.1002/wrna.84. Epub 2011 Mar 14.|
|PMID: 21957044 [PubMed - in process]|
Methods for in-depth genome-wide characterization of transcriptomes and quantification of transcript levels using various microarray and next-generation sequencing technologies have emerged as valuable tools for understanding cellular physiology and human disease biology and have begun to be utilized in various clinical diagnostic applications. Current methods, however, typically require RNA to be converted to complementary DNA prior to measurements. This step has been shown to introduce many biases and artifacts. In order to best characterize the 'true' transcriptome, the single-molecule direct RNA sequencing (DRS) technology was developed. This review focuses on the underlying principles behind the DRS, sample preparation steps, and the current and novel avenues of research and applications DRS offers. WIREs RNA 2011 2 565-570 DOI: 10.1002/wrna.84 For further resources related to this article, please visit the WIREs website.
|5.||Comparison of solution-based exome capture methods for next generation sequencing.|
|Sulonen AM, Ellonen P, Almusa H, Lepisto M, Eldfors S, Hannula S, Miettinen T, Tyynismaa H, Salo P, Heckman C, Joensuu H, Raivio T, Suomalainen A, Saarela J.|
|Genome Biol. 2011 Sep 28;12(9):R94. [Epub ahead of print]|
Techniques enabling targeted re-sequencing of the protein coding sequences of the human genome on next generation sequencing instruments are of great interest. We conducted a systematic comparison of the solution-based exome capture kits provided by Agilent and Roche NimbleGen. A control DNA sample was captured with all four capture methods and prepared for Illumina GAII sequencing. Sequence data from additional samples prepared with the same protocols were also used in the comparison.
We developed a bioinformatics pipeline for quality control, short read alignment, variant identification and annotation of the sequence data. In our analysis, larger percentage of the high quality reads from the NimbleGen captures than from the Agilent captures aligned to the capture target regions. High GC-content of the target sequence was associated with poor capture success in all exome enrichment methods. Comparison of mean allele balances for heterozygous variants indicated a tendency to have more reference bases than variant bases in the heterozygous variant positions within the target regions in all methods. There was virtually no difference in the genotype concordance compared to genotypes derived from SNP arrays. A minimum of 11x coverage was required to make a heterozygote genotype call with 99% accuracy when compared to common SNPs on GWA arrays.
Libraries captured with NimbleGen kits aligned more accurately to the target regions. The updated NimbleGen kit most efficiently covered the exome with a minimum coverage of 20x, yet none of the kits captured all the Consensus Coding Sequence annotated exons.
|PMID: 21955854 [PubMed - as supplied by publisher]|