Biology subjects

Joergensen, M. E.

Publications and source records attributed to Joergensen, M. E..

4 recordsLinked to original sources

bioRxiv2024

eProbe: a capture probe design toolkit for genetic diversity reconstructions from ancient environmental DNA

Ancient environmental DNA (aeDNA) is now commonly used in paleoecology and evolutionary ecology, yet due to difficulties in gaining sufficient genome coverage on individual species from metagenome data, its genetic perspectives remain largely uninvestigated. Hybridization capture has proven as an effective approach for enriching the DNA of target species, thus increasing the genome coverage of sequencing data and enabling population and evolutionary genetics analysis. However, to date there is no tool available for designing capture probe sets tailored for aeDNA based population genetics. Here we present eProbe, an efficient, flexible and easy-to-use program toolkit that provides a complete workflow for capture probe design, assessment and validation. By benchmarking a probe set for foxtail millet, an annual grass, made by the eProbe workflow, we demonstrate a remarkable increase of capturing efficiency, with the target taxa recovery rate improved by 577-fold, and the genome coverage achieved by soil capture-sequencing data even higher than data directly shotgun sequenced from the plant tissues. Probes that underwent our filtering panels show notably higher efficiency. The capture sequencing data enabled accurate population and evolutionary genetic analysis, by effectively inferring the fine-scale genetic structures and patterns, as well as the genotypes on functional genes.

bioinformatics↗

bioRxiv2021

FIND-IT: Ultrafast mining of genome diversity

Novel crop improvement methodologies, including the exploitation of natural genetic variation, are urgently required to feed our rapidly growing human population in the context of global climate change. Here we describe a Fast Identification of Nucleotide variants by DigITal PCR (FIND-IT) method for the rapid identification of pre-targeted genetic variants or rare alleles in large genomic populations. Libraries of 500,000 individuals can be screened and desired variants isolated within two weeks. FIND-IT is widely applicable for mining valuable diversity in any genomic population, including elite breeding and wild germplasm collections. The method provides single nucleotide resolution that has been validated by identifying and isolating knockout lines, non-synonymous codon changes and variants of miRNA and transcription factor binding sites in the agronomically important crop barley. In contrast to existing methods, FIND-IT does not require transformation, cloning or enzymatic steps, and is exempt from GMO regulations. Thus, FIND-IT can be applied immediately to elite crop cultivars and can be tailored to minimize or eliminate time-consuming backcrossing requirements.

genetics↗

bioRxiv2019

Estimating narrow-sense heritability from genome-wide data in admixed populations

Finding an efficient framework for estimating total narrow-sense heritability in admixed populations remains an open question. In this work, we used extensive simulations to evaluate existing linear mixed model frameworks in estimating total narrow-sense heritability in two population-based cohorts from Greenland and compared the results to data from unadmixed individuals from Denmark. When our analysis focused on Greenlandic sib pairs, the model with two relationship matrices, one capturing identity by descent and one capturing identity by state, returned heritability estimates close to the true simulated value, while using each of the two matrices alone led to downward biases. When phenotypes correlated with ancestry, heritability estimates were inflated. Based on these observations, we propose a post-estimation PCA-based adjustment that recovers successfully the true simulated heritability. We use this knowledge to estimate the heritability of ten quantitative traits from the two Greenlandic cohorts and report differences such as lower heritability for height in Greenlanders compared to Europeans. In conclusion, narrow-sense heritability in admixed populations is best estimated using a mixture of genetic relationship matrices on individuals with at least one first-degree relative included in the sample.

genetics↗

bioRxiv2018

Exome-wide association study on Albuminuria identifies a novel rare variant in CUBN and additional genes, in 33,985 Europeans with and without diabetes

Identifying rare coding variants associated with albuminuria may open new avenues for preventing chronic kidney disease (CKD) and end-stage renal disease which are highly prevalent in patients with diabetes. Efforts to identify genetic susceptibility variants for albuminuria have so far been limited with the majority of studies focusing on common variants.\n\nWe performed an exome-wide association study to identify coding variants in a two phase (discovery and replication) approach, totaling to 33,985 individuals of European ancestry (15,872 with and 18,113 without diabetes) and further testing in Greenlanders (n = 2,605). We identify a rare (MAF: 0.8%) missense (A1690V) variant in CUBN (rs141640975, {beta}=0.27, p=1.3 x 10-11) associated with albuminuria as a continuous measure in the combined European meta-analyses. Presence of each rare allele of the variant was associated with a 6.4% increase in albuminuria. The rare CUBN variant had 3 times stronger effect in individuals with diabetes compared to those without (pinteraction: 5.4 x 10-4, {beta}DM: 0.69, {beta}nonDM: 0.20) in the discovery meta-analyses. Geneaggregate tests based on rare and common variants identify three additional genes associated with albuminuria (HES1, CDC73, and GRM5) after multiple testing correction (P_bonferroni<2.7 x 10-6).\n\nThe current study identifies a rare coding variant in the CUBN locus and other potential genes associated with albuminuria in individuals with and without diabetes. These genes have been implicated in renal and cardiovascular dysfunction. These findings provide new insights into the genetic architecture of albuminuria and highlight novel target genes and pathways for prevention of diabetes-related kidney disease.\n\nSignificance statementIncreased albuminuria is a key manifestation of major health burdens, including chronic kidney disease and/or cardiovascular disease. Although being partially heritable, there is a lack of knowledge on rare genetic variants that contribute to albuminuria. The current study describes the discovery and validation, of a new rare gene mutation (~1%) in the CUBN gene which associates with increased albuminuria. Its effect multiplies 3 folds among diabetes cases compared to non diabetic individuals. The study further uncovers 3 additional genes modulating albuminuria levels in humans. Thus the current study findings provide new insights into the genetic architecture of albuminuria and highlight novel genes/pathways for prevention of diabetes related kidney disease.

genetics↗