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1. lordFAST: sensitive and Fast Alignment Search Tool for LOng noisy Read sequencing Data

   https://doi.org/10.1093/bioinformatics/bty544  

   Haghshenas, Ehsan ; Sahinalp, S. Cenk ; Hach, Faraz ; Berger, ed., Bonnie ( July 2018 , Bioinformatics)

   Recent advances in genomics and precision medicine have been made possible through the application of high throughput sequencing (HTS) to large collections of human genomes. Although HTS technologies have proven their use in cataloging human genome variation, computational analysis of the data they generate is still far from being perfect. The main limitation of Illumina and other popular sequencing technologies is their short read length relative to the lengths of (common) genomic repeats. Newer (single molecule sequencing – SMS) technologies such as Pacific Biosciences and Oxford Nanopore are producing longer reads, making it theoretically possible to overcome the difficulties imposed by repeat regions. Unfortunately, because of their high sequencing error rate, reads generated by these technologies are very difficult to work with and cannot be used in many of the standard downstream analysis pipelines. Note that it is not only difficult to find the correct mapping locations of such reads in a reference genome, but also to establish their correct alignment so as to differentiate sequencing errors from real genomic variants. Furthermore, especially since newer SMS instruments provide higher throughput, mapping and alignment need to be performed much faster than before, maintaining high sensitivity.

   We introduce lordFAST, a novel long-read mapper that is specifically designed to align reads generated by PacBio and potentially other SMS technologies to a reference. lordFAST not only has higher sensitivity than the available alternatives, it is also among the fastest and has a very low memory footprint.

   lordFAST is implemented in C++ and supports multi-threading. The source code of lordFAST is available at https://github.com/vpc-ccg/lordfast.

   Supplementary data are available at Bioinformatics online.

    

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2. Genome-wide alignment-free phylogenetic distance estimation under a no strand-bias model

   https://doi.org/10.1093/bioadv/vbac055  

   Balaban, Metin ; Bristy, Nishat Anjum ; Faisal, Ahnaf ; Bayzid, Md Shamsuzzoha ; Mirarab, Siavash ; Lengauer, ed., Thomas ( August 2022 , Bioinformatics Advances)

   Summary: While alignment has been the dominant approach for determining homology prior to phylogenetic inference, alignment-free methods can simplify the analysis, especially when analyzing genome-wide data. Furthermore, alignment-free methods present the only option for emerging forms of data, such as genome skims, which do not permit assembly. Despite the appeal, alignment-free methods have not been competitive with alignment-based methods in terms of accuracy. One limitation of alignment-free methods is their reliance on simplified models of sequence evolution such as Jukes–Cantor. If we can estimate frequencies of base substitutions in an alignment-free setting, we can compute pairwise distances under more complex models. However, since the strand of DNA sequences is unknown for many forms of genome-wide data, which arguably present the best use case for alignment-free methods, the most complex models that one can use are the so-called no strand-bias models. We show how to calculate distances under a four-parameter no strand-bias model called TK4 without relying on alignments or assemblies. The main idea is to replace letters in the input sequences and recompute Jaccard indices between k-mer sets. However, on larger genomes, we also need to compute the number of k-mer mismatches after replacement due to random chance as opposed to homology. We show in simulation that alignment-free distances can be highly accurate when genomes evolve under the assumed models and study the accuracy on assembled and unassembled biological data.

   Our software is available open source at https://github.com/nishatbristy007/NSB.

   Supplementary data are available at Bioinformatics Advances online.

    

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3. Markov chains improve the significance computation of overlapping genome annotations

   https://doi.org/10.1093/bioinformatics/btac255  

   Gafurov, Askar ; Brejová, Broňa ; Medvedev, Paul ( June 2022 , Bioinformatics)

   Genome annotations are a common way to represent genomic features such as genes, regulatory elements or epigenetic modifications. The amount of overlap between two annotations is often used to ascertain if there is an underlying biological connection between them. In order to distinguish between true biological association and overlap by pure chance, a robust measure of significance is required. One common way to do this is to determine if the number of intervals in the reference annotation that intersect the query annotation is statistically significant. However, currently employed statistical frameworks are often either inefficient or inaccurate when computing P-values on the scale of the whole human genome.

   We show that finding the P-values under the typically used ‘gold’ null hypothesis is NP-hard. This motivates us to reformulate the null hypothesis using Markov chains. To be able to measure the fidelity of our Markovian null hypothesis, we develop a fast direct sampling algorithm to estimate the P-value under the gold null hypothesis. We then present an open-source software tool MCDP that computes the P-values under the Markovian null hypothesis in O(m2+n) time and O(m) memory, where m and n are the numbers of intervals in the reference and query annotations, respectively. Notably, MCDP runtime and memory usage are independent from the genome length, allowing it to outperform previous approaches in runtime and memory usage by orders of magnitude on human genome annotations, while maintaining the same level of accuracy.

   The software is available at https://github.com/fmfi-compbio/mc-overlaps. All data for reproducibility are available at https://github.com/fmfi-compbio/mc-overlaps-reproducibility.

   Supplementary data are available at Bioinformatics online.

    

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4. Optimizing de novo genome assembly from PCR-amplified metagenomes

   https://doi.org/10.7717/peerj.6902  

   Roux, Simon ; Trubl, Gareth ; Goudeau, Danielle ; Nath, Nandita ; Couradeau, Estelle ; Ahlgren, Nathan A. ; Zhan, Yuanchao ; Marsan, David ; Chen, Feng ; Fuhrman, Jed A. ; et al ( May 2019 , PeerJ)

   Metagenomics has transformed our understanding of microbial diversity across ecosystems, with recent advances enablingde novoassembly of genomes from metagenomes. These metagenome-assembled genomes are critical to provide ecological, evolutionary, and metabolic context for all the microbes and viruses yet to be cultivated. Metagenomes can now be generated from nanogram to subnanogram amounts of DNA. However, these libraries require several rounds of PCR amplification before sequencing, and recent data suggest these typically yield smaller and more fragmented assemblies than regular metagenomes.

   Here we evaluatede novoassembly methods of 169 PCR-amplified metagenomes, including 25 for which an unamplified counterpart is available, to optimize specific assembly approaches for PCR-amplified libraries. We first evaluated coverage bias by mapping reads from PCR-amplified metagenomes onto reference contigs obtained from unamplified metagenomes of the same samples. Then, we compared different assembly pipelines in terms of assembly size (number of bp in contigs ≥ 10 kb) and error rates to evaluate which are the best suited for PCR-amplified metagenomes.

   Read mapping analyses revealed that the depth of coverage within individual genomes is significantly more uneven in PCR-amplified datasets versus unamplified metagenomes, with regions of high depth of coverage enriched in short inserts. This enrichment scales with the number of PCR cycles performed, and is presumably due to preferential amplification of short inserts. Standard assembly pipelines are confounded by this type of coverage unevenness, so we evaluated other assembly options to mitigate these issues. We found that a pipeline combining read deduplication and an assembly algorithm originally designed to recover genomes from libraries generated after whole genome amplification (single-cell SPAdes) frequently improved assembly of contigs ≥10 kb by 10 to 100-fold for low input metagenomes.

   PCR-amplified metagenomes have enabled scientists to explore communities traditionally challenging to describe, including some with extremely low biomass or from which DNA is particularly difficult to extract. Here we show that a modified assembly pipeline can lead to an improvedde novogenome assembly from PCR-amplified datasets, and enables a better genome recovery from low input metagenomes.

    

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5. A super-pangenome of the North American wild grape species

   https://doi.org/10.1186/s13059-023-03133-2  

   Cochetel, Noé ; Minio, Andrea ; Guarracino, Andrea ; Garcia, Jadran F. ; Figueroa-Balderas, Rosa ; Massonnet, Mélanie ; Kasuga, Takao ; Londo, Jason P. ; Garrison, Erik ; Gaut, Brandon S. ; et al ( December 2023 , Genome Biology)

   Capturing the genetic diversity of wild relatives is crucial for improving crops because wild species are valuable sources of agronomic traits that are essential to enhance the sustainability and adaptability of domesticated cultivars. Genetic diversity across a genus can be captured in super-pangenomes, which provide a framework for interpreting genomic variations.

   Here we report the sequencing, assembly, and annotation of nine wild North American grape genomes, which are phased and scaffolded at chromosome scale. We generate a reference-unbiased super-pangenome using pairwise whole-genome alignment methods, revealing the extent of the genomic diversity among wild grape species from sequence to gene level. The pangenome graph captures genomic variation between haplotypes within a species and across the different species, and it accurately assesses the similarity of hybrids to their parents. The species selected to build the pangenome are a great representation of the genus, as illustrated by capturing known allelic variants in the sex-determining region and for Pierce’s disease resistance loci. Using pangenome-wide association analysis, we demonstrate the utility of the super-pangenome by effectively mapping short reads from genus-wide samples and identifying loci associated with salt tolerance in natural populations of grapes.

   This study highlights how a reference-unbiased super-pangenome can reveal the genetic basis of adaptive traits from wild relatives and accelerate crop breeding research.

    

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