scholarly journals AFLAP: Assembly-Free Linkage Analysis Pipeline using k-mers from whole genome sequencing data

2020 ◽  
Author(s):  
Kyle Fletcher ◽  
Lin Zhang ◽  
Juliana Gil ◽  
Rongkui Han ◽  
Keri Cavanaugh ◽  
...  
Keyword(s):  
Linkage Analysis ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Genetic Map ◽  
Genotyping By Sequencing ◽  
Genetic Maps ◽  
Whole Genome ◽  
Sequencing Data ◽  
Analysis Pipeline ◽  
Genome Assemblies

AbstractBackgroundGenetic maps are an important resource for validation of genome assemblies, trait discovery, and breeding. Next generation sequencing has enabled production of high-density genetic maps constructed with 10,000s of markers. Most current approaches require a genome assembly to identify markers. Our Assembly Free Linkage Analysis Pipeline (AFLAP) removes this requirement by using uniquely segregating k-mers as markers to rapidly construct a genotype table and perform subsequent linkage analysis. This avoids potential biases including preferential read alignment and variant calling.ResultsThe performance of AFLAP was determined in simulations and contrasted to a conventional workflow. We tested AFLAP using 100 F2 individuals of Arabidopsis thaliana, sequenced to low coverage. Genetic maps generated using k-mers contained over 130,000 markers that were concordant with the genomic assembly. The utility of AFLAP was then demonstrated by generating an accurate genetic map using genotyping-by-sequencing data of 235 recombinant inbred lines of Lactuca spp. AFLAP was then applied to 83 F1 individuals of the oomycete Bremia lactucae, sequenced to >5x coverage. The genetic map contained over 90,000 markers ordered in 19 large linkage groups. This genetic map was used to fragment, order, orient, and scaffold the genome, resulting in a much-improved reference assembly.ConclusionsAFLAP can be used to generate high density linkage maps and improve genome assemblies of any organism when a mapping population is available using whole genome sequencing or genotyping-by-sequencing data. Genetic maps produced for B. lactucae were accurately aligned to the genome and guided significant improvements of the reference assembly.

scholarly journals AFLAP: assembly-free linkage analysis pipeline using k-mers from genome sequencing data

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Kyle Fletcher ◽  
Lin Zhang ◽  
Juliana Gil ◽  
Rongkui Han ◽  
Keri Cavanaugh ◽  
...  
Keyword(s):  
Linkage Analysis ◽  
Genome Sequencing ◽  
Genome Assembly ◽  
Simulated Data ◽  
Genetic Maps ◽  
Sequencing Data ◽  
Analysis Pipeline ◽  
A Genome ◽  
Genotype By Sequencing ◽  
Genome Assemblies

AbstractOur assembly-free linkage analysis pipeline (AFLAP) identifies segregating markers as k-mers in the raw reads without using a reference genome assembly for calling variants and provides genotype tables for the construction of unbiased, high-density genetic maps without a genome assembly. AFLAP is validated and contrasted to a conventional workflow using simulated data. AFLAP is applied to whole genome sequencing and genotype-by-sequencing data of F1, F2, and recombinant inbred populations of two different plant species, producing genetic maps that are concordant with genome assemblies. The AFLAP-based genetic map for Bremia lactucae enables the production of a chromosome-scale genome assembly.

scholarly journals Darwin’s Fancy Revised: An Updated Understanding of the Genomic Constitution of Pigeon Breeds

2020 ◽  
Vol 12 (3) ◽  
pp. 136-150
Author(s):  
George Pacheco ◽  
Hein van Grouw ◽  
Michael D Shapiro ◽  
Marcus Thomas P Gilbert ◽  
Filipe Garrett Vieira
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Phenotypic Diversity ◽  
Genotyping By Sequencing ◽  
Columba Livia ◽  
Whole Genome Sequencing Data ◽  
Evolutionary Relationships ◽  
Whole Genome ◽  
Sequencing Data ◽  
Domestic Species

Abstract Through its long history of artificial selection, the rock pigeon (Columba livia Gmelin 1789) was forged into a large number of domestic breeds. The incredible amount of phenotypic diversity exhibited in these breeds has long held the fascination of scholars, particularly those interested in biological inheritance and evolution. However, exploiting them as a model system is challenging, as unlike with many other domestic species, few reliable records exist about the origins of, and relationships between, each of the breeds. Therefore, in order to broaden our understanding of the complex evolutionary relationships among pigeon breeds, we generated genome-wide data by performing the genotyping-by-sequencing (GBS) method on close to 200 domestic individuals representing over 60 breeds. We analyzed these GBS data alongside previously published whole-genome sequencing data, and this combined analysis allowed us to conduct the most extensive phylogenetic analysis of the group, including two feral pigeons and one outgroup. We improve previous phylogenies, find considerable population structure across the different breeds, and identify unreported interbreed admixture events. Despite the reduced number of loci relative to whole-genome sequencing, we demonstrate that GBS data provide sufficient analytical power to investigate intertwined evolutionary relationships, such as those that are characteristic of animal domestic breeds. Thus, we argue that future studies should consider sequencing methods akin to the GBS approach as an optimal cost-effective approach for addressing complex phylogenies.

scholarly journals High-precision and cost-efficient sequencing for real-time COVID-19 surveillance

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sung Yong Park ◽  
Gina Faraci ◽  
Pamela M. Ward ◽  
Jane F. Emerson ◽  
Ha Youn Lee
Keyword(s):  
Los Angeles ◽  
Whole Genome Sequencing ◽  
Real Time ◽  
Genome Sequencing ◽  
High Precision ◽  
High Throughput Sequencing ◽  
Whole Genome ◽  
Sequencing Data ◽  
Public Health Response ◽  
Cost Efficient

AbstractCOVID-19 global cases have climbed to more than 33 million, with over a million total deaths, as of September, 2020. Real-time massive SARS-CoV-2 whole genome sequencing is key to tracking chains of transmission and estimating the origin of disease outbreaks. Yet no methods have simultaneously achieved high precision, simple workflow, and low cost. We developed a high-precision, cost-efficient SARS-CoV-2 whole genome sequencing platform for COVID-19 genomic surveillance, CorvGenSurv (Coronavirus Genomic Surveillance). CorvGenSurv directly amplified viral RNA from COVID-19 patients’ Nasopharyngeal/Oropharyngeal (NP/OP) swab specimens and sequenced the SARS-CoV-2 whole genome in three segments by long-read, high-throughput sequencing. Sequencing of the whole genome in three segments significantly reduced sequencing data waste, thereby preventing dropouts in genome coverage. We validated the precision of our pipeline by both control genomic RNA sequencing and Sanger sequencing. We produced near full-length whole genome sequences from individuals who were COVID-19 test positive during April to June 2020 in Los Angeles County, California, USA. These sequences were highly diverse in the G clade with nine novel amino acid mutations including NSP12-M755I and ORF8-V117F. With its readily adaptable design, CorvGenSurv grants wide access to genomic surveillance, permitting immediate public health response to sudden threats.

scholarly journals Whole genome sequencing reveals high differentiation, low levels of genetic diversity and short runs of homozygosity among Swedish wels catfish

Heredity ◽  
2021 ◽  
Author(s):  
Axel Jensen ◽  
Mette Lillie ◽  
Kristofer Bergström ◽  
Per Larsson ◽  
Jacob Höglund
Keyword(s):  
Genetic Diversity ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome Sequencing Data ◽  
Peripheral Populations ◽  
Whole Genome ◽  
Runs Of Homozygosity ◽  
Sequencing Data ◽  
Isolated Populations ◽  
Native Populations

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.

scholarly journals Estimating sequencing error rates using families

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Kelley Paskov ◽  
Jae-Yoon Jung ◽  
Brianna Chrisman ◽  
Nate T. Stockham ◽  
Peter Washington ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Exome Sequencing ◽  
Genome Sequencing ◽  
Variant Calling ◽  
Error Rates ◽  
Sequencing Error ◽  
Whole Genome ◽  
Sequencing Data ◽  
Sequencing Platform ◽  
Whole Exome

Abstract Background As next-generation sequencing technologies make their way into the clinic, knowledge of their error rates is essential if they are to be used to guide patient care. However, sequencing platforms and variant-calling pipelines are continuously evolving, making it difficult to accurately quantify error rates for the particular combination of assay and software parameters used on each sample. Family data provide a unique opportunity for estimating sequencing error rates since it allows us to observe a fraction of sequencing errors as Mendelian errors in the family, which we can then use to produce genome-wide error estimates for each sample. Results We introduce a method that uses Mendelian errors in sequencing data to make highly granular per-sample estimates of precision and recall for any set of variant calls, regardless of sequencing platform or calling methodology. We validate the accuracy of our estimates using monozygotic twins, and we use a set of monozygotic quadruplets to show that our predictions closely match the consensus method. We demonstrate our method’s versatility by estimating sequencing error rates for whole genome sequencing, whole exome sequencing, and microarray datasets, and we highlight its sensitivity by quantifying performance increases between different versions of the GATK variant-calling pipeline. We then use our method to demonstrate that: 1) Sequencing error rates between samples in the same dataset can vary by over an order of magnitude. 2) Variant calling performance decreases substantially in low-complexity regions of the genome. 3) Variant calling performance in whole exome sequencing data decreases with distance from the nearest target region. 4) Variant calls from lymphoblastoid cell lines can be as accurate as those from whole blood. 5) Whole-genome sequencing can attain microarray-level precision and recall at disease-associated SNV sites. Conclusion Genotype datasets from families are powerful resources that can be used to make fine-grained estimates of sequencing error for any sequencing platform and variant-calling methodology.

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