Microfluidic Amplification as a Tool for Massive Parallel Sequencing of Familial Hypercholesterolemia Genes.

Clin Chem. 2012 Jan 31;

Authors: Hollants S, Redeker EJ, Matthijs G

Abstract
BACKGROUND:Familial hypercholesterolemia (FH) is an autosomal dominant disorder that affects cholesterol metabolism and is an important risk factor for heart disease. Three different genes were causally linked to this disorder: LDLR (low density lipoprotein receptor), APOB [apolipoprotein B (including Ag(x) antigen)], and PCSK9 (proprotein convertase subtilisin/kexin type 9). We evaluated a new amplicon preparation tool for resequencing these genes on next generation sequencing (NGS) platforms.METHODS:For the 3 genes, 38 primer pairs were designed and loaded on the Fluidigm Access Array, a microfluidic array in which a PCR was performed. We amplified 144 DNA samples (73 positive controls and 71 patient samples) and performed 3 sequencing runs on a GS FLX Titanium system from Roche 454, using pyrosequencing. Data were analyzed with the SeqNext module of the Sequence Pilot software.RESULT:From the 38 amplicons, 37 were amplified successfully, without any further optimization. Sequencing resulted in a mean coverage of the individual amplicons of 71-fold, 74-fold, and 117-fold for the 3 runs, respectively. In the positive controls, all known mutations were identified. In 29% of the patient samples, a pathogenic point mutation or small deletion/insertion was found. Large rearrangements were not detectable with NGS, but were picked up by multiplex ligation-dependent probe amplification.CONCLUSIONS:Combining a microfluidic amplification system with massive parallel sequencing is an effective method for mutation scanning in FH patients, which can be implemented in diagnostics. For data analysis, we propose a minimum variant frequency threshold of 20% and a minimum coverage of 25-fold.

PMID: 22294733 [PubMed - as supplied by publisher]

Development and mapping of SNP assays in allotetraploid cotton.

Theor Appl Genet. 2012 Jan 18;

Authors: Byers RL, Harker DB, Yourstone SM, Maughan PJ, Udall JA

Abstract
A narrow germplasm base and a complex allotetraploid genome have made the discovery of single nucleotide polymorphism (SNP) markers difficult in cotton (Gossypium hirsutum). To generate sequence for SNP discovery, we conducted a genome reduction experiment (EcoRI, BafI double digest, followed by adapter ligation, biotin-streptavidin purification, and agarose gel separation) on two accessions of G. hirsutum and two accessions of G. barbadense. From the genome reduction experiment, a total of 2.04 million genomic sequence reads were assembled into contigs with an N(50) of 508 bp and analyzed for SNPs. A previously generated assembly of expressed sequence tags (ESTs) provided an additional source for SNP discovery. Using highly conservative parameters (minimum coverage of 8× at each SNP and 20% minor allele frequency), a total of 11,834 and 1,679 non-genic SNPs were identified between accessions of G. hirsutum and G. barbadense in genome reduction assemblies, respectively. An additional 4,327 genic SNPs were also identified between accessions of G. hirsutum in the EST assembly. KBioscience KASPar assays were designed for a portion of the intra-specific G. hirsutum SNPs. From 704 non-genic and 348 genic markers developed, a total of 367 (267 non-genic, 100 genic) mapped in a segregating F(2) population (Acala Maxxa × TX2094) using the Fluidigm EP1 system. A G. hirsutum genetic linkage map of 1,688 cM was constructed based entirely on these new SNP markers. Of the genic-based SNPs, we were able to identify within which genome ('A' or 'D') each SNP resided using diploid species sequence data. Genetic maps generated by these newly identified markers are being used to locate quantitative, economically important regions within the cotton genome.

PMID: 22252442 [PubMed - as supplied by publisher]

Comprehensive qPCR profiling of gene expression in single neuronal cells.

Nat Protoc. 2012;7(1):118-27

Authors: Citri A, Pang ZP, Südhof TC, Wernig M, Malenka RC

Abstract
A major challenge in neuronal stem cell biology lies in characterization of lineage-specific reprogrammed human neuronal cells, a process that necessitates the use of an assay sensitive to the single-cell level. Single-cell gene profiling can provide definitive evidence regarding the conversion of one cell type into another at a high level of resolution. The protocol we describe uses Fluidigm Biomark dynamic arrays for high-throughput expression profiling from single neuronal cells, assaying up to 96 independent samples with up to 96 quantitative PCR (qPCR) probes (equivalent to 9,216 reactions) in a single experiment, which can be completed within 2-3 d. The protocol enables simple and cost-effective profiling of several hundred transcripts from a single cell, and it could have numerous utilities.

PMID: 22193304 [PubMed - in process]

Expression levels of 25 genes in liver and testis located in a QTL region for androstenone on SSC7q1.2.

Anim Genet. 2011 Dec;42(6):662-5

Authors: Robic A, Fève K, Larzul C, Billon Y, van Son M, Liaubet L, Sarry J, Milan D, Grindflek E, Bidanel JP, Riquet J

Abstract
A quantitative trait locus (QTL) for boar fat androstenone levels has been identified near the SSC7 centromere in a Large White × Meishan cross. Backcrosses were produced to isolate the Chinese haplotype in a European genetic background. The expression of 25 genes from the QTL region was studied in the testes and livers of 5-month-old backcross boars, with the aim of identifying the causal gene. Using Fluidigm, a new high-throughput technology, the expression of 25 genes was measured in a single real-time PCR experiment. This study found six significantly down-regulated genes (C6ORF106, C6ORF81, CLPS, SLC26A8, SRPK1 and MAPK14) in the testes of MS-LW backcross boars. However, according to current knowledge, none of the genes appear to be related to androstenone metabolism. In the livers, none of the genes were significantly up- or down-regulated, including TEAD3, which was previously designated as a possible candidate to explain this QTL.

PMID: 22035010 [PubMed - in process]