June 1, 2021  |  

The resurgence of reference quality genome

Several new 3rd generation long-range DNA sequencing and mapping technologies have recently become available that are starting to create a resurgence in genome sequence quality. Unlike their 2nd generation, shortread counterparts that can resolve a few hundred or a few thousand basepairs, the new technologies can routinely sequence 10,000 bp reads or map across 100,000 bp molecules. The substantially greater lengths are being used to enhance a number of important problems in genomics and medicine, including de novo genome assembly, structural variation detection, and haplotype phasing. Here we discuss the capabilities of the latest technologies, and show how they will improve the “3Cs of Genome Assembly”: the contiguity, completeness, and correctness. We derive this analysis from (1) a metaanalysis of the currently available 3rd generation genome assemblies, (2) a retrospective analysis of the evolution of the reference human genome, and (3) extensive simulations with dozens of species across the tree of life. We also propose a model using support vector regression (SVR) that predicts genome assembly performance using four features: read lengths(L) and coverage values(C) that can be used for evaluating potential technologies along with genome size(G) and repeats(R) that present species specific characteristics. The proposed model significantly improves genome assembly performance prediction by adopting data-driven approach and addressing limitations of the previous hypothesis-driven methodology. Overall, we anticipate these technologies unlock the genomic “dark matter”, and provide many new insights into evolution, agriculture, and human diseases.


June 1, 2021  |  

Characterizing the pan-genome of maize with PacBio SMRT Sequencing

Maize is an amazingly diverse crop. A study in 20051 demonstrated that half of the genome sequence and one-third of the gene content between two inbred lines of maize were not shared. This diversity, which is more than two orders of magnitude larger than the diversity found between humans and chimpanzees, highlights the inability of a single reference genome to represent the full pan-genome of maize and all its variants. Here we present and review several efforts to characterize the complete diversity within maize using the highly accurate long reads of PacBio Single Molecule, Real-Time (SMRT) Sequencing. These methods provide a framework for a pan-genomic approach that can be applied to studies of a wide variety of important crop species.


April 21, 2020  |  

Discovery of tandem and interspersed segmental duplications using high-throughput sequencing.

Several algorithms have been developed that use high-throughput sequencing technology to characterize structural variations (SVs). Most of the existing approaches focus on detecting relatively simple types of SVs such as insertions, deletions and short inversions. In fact, complex SVs are of crucial importance and several have been associated with genomic disorders. To better understand the contribution of complex SVs to human disease, we need new algorithms to accurately discover and genotype such variants. Additionally, due to similar sequencing signatures, inverted duplications or gene conversion events that include inverted segmental duplications are often characterized as simple inversions, likewise, duplications and gene conversions in direct orientation may be called as simple deletions. Therefore, there is still a need for accurate algorithms to fully characterize complex SVs and thus improve calling accuracy of more simple variants.We developed novel algorithms to accurately characterize tandem, direct and inverted interspersed segmental duplications using short read whole genome sequencing datasets. We integrated these methods to our TARDIS tool, which is now capable of detecting various types of SVs using multiple sequence signatures such as read pair, read depth and split read. We evaluated the prediction performance of our algorithms through several experiments using both simulated and real datasets. In the simulation experiments, using a 30× coverage TARDIS achieved 96% sensitivity with only 4% false discovery rate. For experiments that involve real data, we used two haploid genomes (CHM1 and CHM13) and one human genome (NA12878) from the Illumina Platinum Genomes set. Comparison of our results with orthogonal PacBio call sets from the same genomes revealed higher accuracy for TARDIS than state-of-the-art methods. Furthermore, we showed a surprisingly low false discovery rate of our approach for discovery of tandem, direct and inverted interspersed segmental duplications prediction on CHM1 (<5% for the top 50 predictions).TARDIS source code is available at https://github.com/BilkentCompGen/tardis, and a corresponding Docker image is available at https://hub.docker.com/r/alkanlab/tardis/.Supplementary data are available at Bioinformatics online. © The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.


April 21, 2020  |  

The role of genomic structural variation in the genetic improvement of polyploid crops

Many of our major crop species are polyploids, containing more than one genome or set of chromosomes. Polyploid crops present unique challenges, including difficulties in genome assembly, in discriminating between multiple gene and sequence copies, and in genetic mapping, hindering use of genomic data for genetics and breeding. Polyploid genomes may also be more prone to containing structural variation, such as loss of gene copies or sequences (presence–absence variation) and the presence of genes or sequences in multiple copies (copy-number variation). Although the two main types of genomic structural variation commonly identified are presence–absence variation and copy-number variation, we propose that homeologous exchanges constitute a third major form of genomic structural variation in polyploids. Homeologous exchanges involve the replacement of one genomic segment by a similar copy from another genome or ancestrally duplicated region, and are known to be extremely common in polyploids. Detecting all kinds of genomic structural variation is challenging, but recent advances such as optical mapping and long-read sequencing offer potential strategies to help identify structural variants even in complex polyploid genomes. All three major types of genomic structural variation (presence–absence, copy-number, and homeologous exchange) are now known to influence phenotypes in crop plants, with examples of flowering time, frost tolerance, and adaptive and agronomic traits. In this review, we summarize the challenges of genome analysis in polyploid crops, describe the various types of genomic structural variation and the genomics technologies and data that can be used to detect them, and collate information produced to date related to the impact of genomic structural variation on crop phenotypes. We highlight the importance of genomic structural variation for the future genetic improvement of polyploid crops.


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