Anita Lerch

Dr. Anita Lerch

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Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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9 April 2004 in Science
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Journal Article
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FDFred S. Dietrich
Fred S. Dietrich
SVSylvia Voegeli
Sylvia Voegeli
SBSophie Brachat
Sophie Brachat
ALAnita Lerch
Anita Lerch
KGKrista Gates
Krista Gates
PPPeter Philippsen
Peter Philippsen
We have sequenced and annotated the genome of the filamentous ascomycete Ashbya gossypii . With a size of only 9.2 megabases, encoding 4718 protein-coding genes, it is the smallest genome of a free-living eukaryote yet characterized. More than 90% of A. gossypii genes show both homology and a particular pattern of synteny with Saccharomyces cerevisiae . Analysis of this pattern revealed 300 inversions and translocations that have occurred since divergence of these two species. It also provided compelling evidence that the evolution of S. cerevisiae included a whole genome duplication orfusion of two related species and showed, through inferred ancient gene orders, which of the duplicated genes lost one copy and which retained both copies.

9 December 2014 in Bioinformatics
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Journal Article
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DGDimos Gaidatzis
Dimos Gaidatzis
ALAnita Lerch
Anita Lerch
FHFlorian Hahne
Florian Hahne
MSMichael B. Stadler
Michael B. Stadler
Summary: QuasR is a package for the integrated analysis of high-throughput sequencing data in R, covering all steps from read preprocessing, alignment and quality control to quantification. QuasR supports different experiment types (including RNA-seq, ChIP-seq and Bis-seq) and analysis variants (e.g. paired-end, stranded, spliced and allele-specific), and is integrated in Bioconductor so that its output can be directly processed for statistical analysis and visualization. Availability and implementation: QuasR is implemented in R and C/C++. Source code and binaries for major platforms (Linux, OS X and MS Windows) are available from Bioconductor (www.bioconductor.org/packages/release/bioc/html/QuasR.html). The package includes a ‘vignette’ with step-by-step examples for typical work flows. Contact:michael.stadler@fmi.ch Supplementary information: Supplementary data are available at Bioinformatics online.

13 November 2017 in BMC Genomics
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ALAnita Lerch
Anita Lerch
CKCristian Koepfli
Cristian Koepfli
NHNatalie E. Hofmann
Natalie E. Hofmann
CMCamilla Messerli
Camilla Messerli
SWStephen Wilcox
Stephen Wilcox
IFIngrid Felger
Ingrid Felger
Amplicon deep sequencing permits sensitive detection of minority clones and improves discriminatory power for genotyping multi-clone Plasmodium falciparum infections. New amplicon sequencing and data analysis protocols are needed for genotyping in epidemiological studies and drug efficacy trials of P. falciparum. Targeted sequencing of molecular marker csp and novel marker cpmp was conducted in duplicate on mixtures of parasite culture strains and 37 field samples. A protocol allowing to multiplex up to 384 samples in a single sequencing run was applied. Software “HaplotypR” was developed for data analysis. Cpmp was highly diverse (He = 0.96) in contrast to csp (He = 0.57). Minority clones were robustly detected if their frequency was >1%. False haplotype calls owing to sequencing errors were observed below that threshold. To reliably detect haplotypes at very low frequencies, experiments are best performed in duplicate and should aim for coverage of >10′000 reads/amplicon. When compared to length polymorphic marker msp2, highly multiplexed amplicon sequencing displayed greater sensitivity in detecting minority clones.

25 June 2003 in Genome Biology
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Journal Article
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SBSophie Brachat
Sophie Brachat
FDFred S Dietrich
Fred S Dietrich
SVSylvia Voegeli
Sylvia Voegeli
ZZZhihong Zhang
Zhihong Zhang
LSLarissa Stuart
Larissa Stuart
PPPeter Philippsen
Peter Philippsen
The recently sequenced genome of the filamentous fungus Ashbya gossypii revealed remarkable similarities to that of the budding yeast Saccharomyces cerevisiae both at the level of homology and synteny (conservation of gene order). Thus, it became possible to reinvestigate the S. cerevisiae genome in the syntenic regions leading to an improved annotation. We have identified 23 novel S. cerevisiae open reading frames (ORFs) as syntenic homologs of A. gossypii genes; for all but one, homologs are present in other eukaryotes including humans. Other comparisons identified 13 overlooked introns and suggested 69 potential sequence corrections resulting in ORF extensions or ORF fusions with improved homology to the syntenic A. gossypii homologs. Of the proposed corrections, 25 were tested and confirmed by resequencing. In addition, homologs of nearly 1,000 S. cerevisiae ORFs, presently annotated as hypothetical, were found in A. gossypii at syntenic positions and can therefore be considered as authentic genes. Finally, we suggest that over 400 S. cerevisiae ORFs that overlap other ORFs in S. cerevisiae and for which no homolog can be detected in A. gossypii should be regarded as spurious. Although, the S. cerevisiae genome is rightly considered as one of the most accurately sequenced and annotated eukaryotic genomes, we have shown that it still benefits substantially from comparison to the completed sequence and syntenic gene map of A. gossypii, an evolutionarily related fungus. This type of approach will strongly support the annotation of more complex genomes such as the human and murine genomes.

21 August 2020 in Proceedings of the National Academy of Sciences
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TPT. Alex Perkins
T. Alex Perkins
SCSean M. Cavany
Sean M. Cavany
SMSean M. Moore
Sean M. Moore
RORachel J. Oidtman
Rachel J. Oidtman
ALAnita Lerch
Anita Lerch
MPMarya Poterek
Marya Poterek
Significance: In early 2020, delays in availability of diagnostic testing for COVID-19 prompted questions about the extent of unobserved community transmission in the United States. We quantified unobserved infections in the United States during this time using a stochastic transmission model. Although precision of our estimates is limited, we conclude that many more thousands of people were infected than were reported as cases by the time a national emergency was declared and that fewer than 10% of locally acquired, symptomatic infections in the United States may have been detected over a period of a month. This gap in surveillance during a critical phase of the epidemic resulted in a large, unobserved reservoir of infection in the United States by early March.

28 November 2019 in Scientific Reports
Verified
Journal Article
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MGMaria Gruenberg
Maria Gruenberg
ALAnita Lerch
Anita Lerch
HBHans-Peter Beck
Hans-Peter Beck
IFIngrid Felger
Ingrid Felger
Clinical trials monitoring malaria drug resistance require genotyping of recurrent Plasmodium falciparum parasites to distinguish between treatment failure and new infection occurring during the trial follow up period. Because trial participants usually harbour multi-clonal P. falciparum infections, deep amplicon sequencing (AmpSeq) was employed to improve sensitivity and reliability of minority clone detection. Paired samples from 32 drug trial participants were Illumina deep-sequenced for five molecular markers. Reads were analysed by custom-made software HaplotypR and trial outcomes compared to results from the previous standard genotyping method based on length-polymorphic markers. Diversity of AmpSeq markers in pre-treatment samples was comparable or higher than length-polymorphic markers. AmpSeq was highly reproducible with consistent quantification of co-infecting parasite clones within a host. Outcomes of the three best-performing markers, cpmp, cpp and ama1-D3, agreed in 26/32 (81%) of patients. Discordance between the three markers performed per sample was much lower by AmpSeq (six patients) compared to length-polymorphic markers (eleven patients). Using AmpSeq for discrimination of recrudescence and new infection in antimalarial drug trials provides highly reproducible and robust characterization of clone dynamics during trial follow-up. AmpSeq overcomes limitations inherent to length-polymorphic markers. Regulatory clinical trials of antimalarial drugs will greatly benefit from this unbiased typing method.