scholarly journals Fast and low-cost decentralized surveillance of transmission of tuberculosis based on strain-specific PCRs tailored from whole genome sequencing data: a pilot study

2015 ◽  
Vol 21 (3) ◽  
pp. 249.e1-249.e9 ◽  
Author(s):  
L. Pérez-Lago ◽  
M. Martínez Lirola ◽  
M. Herranz ◽  
I. Comas ◽  
E. Bouza ◽  
...  
2021 ◽  
Vol 22 (12) ◽  
pp. 6224
Author(s):  
Li Yu ◽  
Yanshen Nie ◽  
Jinxia Jiao ◽  
Liufang Jian ◽  
Jie Zhao

A forward genetic approach is a powerful tool for identifying the genes underlying the phenotypes of interest. However, the conventional map-based cloning method is lengthy, requires a large mapping population and confirmation of many candidate genes in a broad genetic region to clone the causal variant. The whole-genome sequencing method clones the variants with a certain failure probability for multiple reasons, especially for heterozygotes, and could not be used to clone the mutation of epigenetic modifications. Here, we applied the highly complementary characteristics of these two methods and developed a sequencing-based mapping method (SBM) for identifying the location of plant variants effectively with a small population and low cost, which is very user-friendly for most popular laboratories. This method used the whole-genome sequencing data of two pooled populations to screen out enough markers. These markers were used to identify and narrow the candidate region by analyzing the marker-indexes and recombinants. Finally, the possible mutational sites were identified using the whole-genome sequencing data and verified in individual mutants. To elaborate the new method, we displayed the cloned processes in one Arabidopsis heterozygous mutant and two rice homozygous mutants. Thus, the sequencing-based mapping method could clone effectively different types of plant mutations and was a powerful tool for studying the functions of plant genes in the species with known genomic sequences.


Heredity ◽  
2021 ◽  
Author(s):  
Axel Jensen ◽  
Mette Lillie ◽  
Kristofer Bergström ◽  
Per Larsson ◽  
Jacob Höglund

AbstractThe use of genetic markers in the context of conservation is largely being outcompeted by whole-genome data. Comparative studies between the two are sparse, and the knowledge about potential effects of this methodology shift is limited. Here, we used whole-genome sequencing data to assess the genetic status of peripheral populations of the wels catfish (Silurus glanis), and discuss the results in light of a recent microsatellite study of the same populations. The Swedish populations of the wels catfish have suffered from severe declines during the last centuries and persists in only a few isolated water systems. Fragmented populations generally are at greater risk of extinction, for example due to loss of genetic diversity, and may thus require conservation actions. We sequenced individuals from the three remaining native populations (Båven, Emån, and Möckeln) and one reintroduced population of admixed origin (Helge å), and found that genetic diversity was highest in Emån but low overall, with strong differentiation among the populations. No signature of recent inbreeding was found, but a considerable number of short runs of homozygosity were present in all populations, likely linked to historically small population sizes and bottleneck events. Genetic substructure within any of the native populations was at best weak. Individuals from the admixed population Helge å shared most genetic ancestry with the Båven population (72%). Our results are largely in agreement with the microsatellite study, and stresses the need to protect these isolated populations at the northern edge of the distribution of the species.


2017 ◽  
Vol 114 (38) ◽  
pp. 10166-10171 ◽  
Author(s):  
Christoph Lippert ◽  
Riccardo Sabatini ◽  
M. Cyrus Maher ◽  
Eun Yong Kang ◽  
Seunghak Lee ◽  
...  

Prediction of human physical traits and demographic information from genomic data challenges privacy and data deidentification in personalized medicine. To explore the current capabilities of phenotype-based genomic identification, we applied whole-genome sequencing, detailed phenotyping, and statistical modeling to predict biometric traits in a cohort of 1,061 participants of diverse ancestry. Individually, for a large fraction of the traits, their predictive accuracy beyond ancestry and demographic information is limited. However, we have developed a maximum entropy algorithm that integrates multiple predictions to determine which genomic samples and phenotype measurements originate from the same person. Using this algorithm, we have reidentified an average of >8 of 10 held-out individuals in an ethnically mixed cohort and an average of 5 of either 10 African Americans or 10 Europeans. This work challenges current conceptions of personal privacy and may have far-reaching ethical and legal implications.


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