Dataset Information

Optimized whole-genome amplification strategy for extremely AT-biased template.

ABSTRACT: Pathogen genome sequencing directly from clinical samples is quickly gaining importance in genetic and medical research studies. However, low DNA yield from blood-borne pathogens is often a limiting factor. The problem worsens in extremely base-biased genomes such as the AT-rich Plasmodium falciparum. We present a strategy for whole-genome amplification (WGA) of low-yield samples from P. falciparum prior to short-read sequencing. We have developed WGA conditions that incorporate tetramethylammonium chloride for improved amplification and coverage of AT-rich regions of the genome. We show that this method reduces amplification bias and chimera formation. Our data show that this method is suitable for as low as 10 pg input DNA, and offers the possibility of sequencing the parasite genome from small blood samples.

SUBMITTER: Oyola SO

PROVIDER: S-EPMC4263299 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Optimized whole-genome amplification strategy for extremely AT-biased template.

Oyola Samuel O SO Manske Magnus M Campino Susana S Claessens Antoine A Hamilton William L WL Kekre Mihir M Drury Eleanor E Mead Daniel D Gu Yong Y Miles Alistair A MacInnis Bronwyn B Newbold Chris C Berriman Matthew M Kwiatkowski Dominic P DP

DNA research : an international journal for rapid publication of reports on genes and genomes 20140919 6

Pathogen genome sequencing directly from clinical samples is quickly gaining importance in genetic and medical research studies. However, low DNA yield from blood-borne pathogens is often a limiting factor. The problem worsens in extremely base-biased genomes such as the AT-rich Plasmodium falciparum. We present a strategy for whole-genome amplification (WGA) of low-yield samples from P. falciparum prior to short-read sequencing. We have developed WGA conditions that incorporate tetramethylammon ...[more]

PMID: 25240466

Similar Datasets

Project description:BACKGROUND:Laron syndrome (LS) is an autosomal recessive hereditary condition affecting only 1/1000000 births. The cause is associated with mutations in the growth hormone (GH) receptor (GHR), leading to GH insensitivity. LS patients typically present with severe growth retardation, obesity, and abnormal sexual maturation. Currently, LS diagnosis is performed post-delivery. Therefore, we assessed the efficiency of Pre-implantation Genetic Testing (PGT) coupled with monoplex-polymerase chain reaction (PCR) technology for detecting this monogenic disease in embryos from a couple confirmed as LS heterozygous carriers. CASE SUMMARY:The couple LS-carriers were confirmed by the presence of a first child born with LS. The couple underwent a standard in vitro fertilization (IVF) protocol. DNA was collected from trophectoderm cells from day 5 embryos. Whole genome amplification (WGA) was performed using a Sureplex DNA Amplification System and analyzed by PCR, targeting the deletion of the exons 5 and 6 in the GHR gene as well as PGT by Next-generation Sequencing (Illumina). Eleven embryos were collected and analyzed. 27.3% were the wild type for GHR, 45.5% were heterozygotes, and 18.2% homozygous mutants. One embryo yielded no results. Three 2-embryos transfers were performed; 2 normal homozygous and four heterozygous carriers were selected for transfer. The first two transfers were unsuccessful, whereas the final transfer with two heterozygous embryos resulted in clinical pregnancy. The genomic composition of the fetus was verified, applying the same techniques using amniocytes, extracted after 21 wk of the ongoing pregnancy. The fetus was confirmed as GHR deletion in exon 5-6, carrier. A non-affected baby was born. CONCLUSION:Here, we present a case demonstrating that using WGA as a template in addition to PCR targeting specific gene regions, exons 5 and 6 on the GHR gene, could identify LS carrier embryos. This provides evidence that WGA and PCR serve as an excellent tool to detect this specific monogenic disease in IVF embryos, thus allowing selection of candidate embryos for transfer successfully when a specific inherited genetic mutation/disease is suspected.

Project description:Sex-biased demographic events ("sex-bias") involve unequal numbers of females and males. These events are typically inferred from the relative amount of X-chromosomal to autosomal genetic variation and have led to conflicting conclusions about human demographic history. Though population size changes alter the relative amount of X-chromosomal to autosomal genetic diversity even in the absence of sex-bias, this has generally not been accounted for in sex-bias estimators to date. Here, we present a novel method to identify sex-bias from genetic sequence data that models population size changes and estimates the female fraction of the effective population size during each time epoch. Compared to recent sex-bias inference methods, our approach can detect sex-bias that changes on a single population branch without requiring data from an outgroup or knowledge of divergence events. When applied to simulated data, conventional sex-bias estimators are biased by population size changes, especially recent growth or bottlenecks, while our estimator is unbiased. We next apply our method to high-coverage exome data from the 1000 Genomes Project and estimate a male bias in Yorubans (47% female) and Europeans (44%), possibly due to stronger background selection on the X chromosome than on the autosomes. Finally, we apply our method to the 1000 Genomes Project Phase 3 high-coverage Complete Genomics whole-genome data and estimate a female bias in Yorubans (63% female), Europeans (84%), Punjabis (82%), as well as Peruvians (56%), and a male bias in the Southern Han Chinese (45%). Our method additionally identifies a male-biased migration out of Africa based on data from Europeans (20% female). Our results demonstrate that modeling population size change is necessary to estimate sex-bias parameters accurately. Our approach gives insight into signatures of sex-bias in sexual species, and the demographic models it produces can serve as more accurate null models for tests of selection.

Dataset Information

Optimized whole-genome amplification strategy for extremely AT-biased template.

Publications

Optimized whole-genome amplification strategy for extremely AT-biased template.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets