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opencc-zeroJan 2021View details →

Alignments from: Gene count from target sequence capture places three whole genome duplication events in Hibiscus L. (Malvaceae)

Background: The great diversity in plant genome size and chromosome number is partly due to polyploidization (i.e., genome doubling events). The differences in genome size and chromosome number among diploid plant species can be a window into the intriguing phenomenon of past genome doubling that may be obscured through time by the process of diploidization. The genus Hibiscus L. (Malvaceae) has a wide diversity of chromosome numbers and a complex genomic history. Hibiscus is ideal for exploring past genomic events because although two ancient genome duplication events have been identified, more are likely to be found due to its diversity of chromosome numbers. To reappraise the history of whole genome duplication events, we tested three alternative scenarios describing different polyploidization events. Results: Using target sequence capture, we designed a new probe set for Hibiscus and generated 87 orthologous genes from four diploid species. We detected paralogues in >54% putative single-copy genes. 34 of these genes were selected for testing three different genome duplication scenarios using gene counting. All species of Hibiscus sampled shared one genome duplication with H. syriacus and one whole genome duplication occurred along the branch leading to H. syriacus. Conclusions: Here, we corroborated the independent genome doubling previously found in the lineage leading to H. syriacus and a shared genome doubling of this lineage and the remainder of Hibiscus. Additionally, we found a previously undiscovered genome duplication shared by the /Pavonia and /Malvaviscus clades (both nested within Hibiscus) with the occurrences of two copies in what were otherwise single-copy genes. Our results highlight the complexity of genomic diversity in some plant groups, which makes orthology assessment and accurate phylogenomic inference difficult.

zenodo32/100

Genome alignments from "Split-alignment of genomes finds orthologies more accurately"

Here are the genome alignments resulting from "Split-alignment of genomes finds orthologies more accurately", Genome Biology 2015, 16:106. <ul> <li>In the terminology of that paper, these are 2-split, post-masked alignments.</li> <li>They are in MAF format (http://genome.ucsc.edu/FAQ/FAQformat.html), with "p" lines (http://last.cbrc.jp/doc/last-split.html).</li> <li>Alignments with high ambiguity have not been removed, so if you want unambiguously 1-to-1 alignments, remove those annotated with mismap > 0.00001 or so.</li> <li>The chimp and orangutan alignments were made using the 500/30 gap costs suggested at the end of the paper.</li> </ul>

opencc-zeroMay 2015View details →

zenodo32/100

Genome Alignment of Cancer Sequencing Data

Part of the GTN Cancer Analysis learning Pathway based on the Bioinformatics.ca Cancer Workshop

opencc-by-4.0Apr 2023View details →

zenodo32/100

Enhancing Protein Sequence Annotation in Viral Genomics Using Large Language Models and Soft Alignments.

List of 200 most abundant VOG descriptions.

opencc-by-4.0Jul 2023View details →

publicJan 2021View details →

Alignments from: Gene count from target sequence capture places three whole genome duplication events in Hibiscus L. (Malvaceae)

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publicNov 2020View details →

Genome reduction is associated with bacterial pathogenicity across different scales of temporal and ecological divergence - between species core gene alignments

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publicJun 2020View details →

Supplementary tables S5, S7, S9, S10, original protein models fasta files used for alignments, aligned and manually curated protein modes files used for phylogenies (PHYLIP format), and phylogenetic trees of plant cell wall decomposition gene families from 44 basidiomycete genomes (.tre files)

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publicJun 2020View details →

Nucleotide alignments of eight meiosis genes under extreme selection following whole genome duplication in Arabidopsis lyrata/A.arenosa.

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opencc-by-4.0Sep 2020View details →

Simulated pairs of nucleotide sequences for testing (alignment-free) genome distance estimate methods

This repository contains 24,000 pairs of nucleotide sequences (and associated parameters) that have been simulated for testing alignment-free genome distance estimates. Given an evolutionary distance d varying from 0.05 to 1.00 nucleotide substitutions per character (step = 0.05), the program <a href="http://abacus.gene.ucl.ac.uk/software/indelible/">INDELible</a> was used to simulate the evolution of 200 nucleotide sequence pairs with d substitution events per character under the models GTR and GTR+Γ. Each model was adjusted with three different equilibrium frequencies: <ul> <li>f1: equal frequencies, i.e. freq(A) = freq(C) = freq(G) = freq(T) = 0.25,</li> <li>f2: GC-rich, i.e. freq(A) = 0.1, freq(C) = 0.3, freq(G) = 0.4, freq(T) = 0.2,</li> <li>f3: AT-rich, i.e. freq(A) = freq(T) = 0.4, freq(C) = freq(G) = 0.1.</li> </ul> For each simulated sequence pair, model parameters (i.e. GTR: six relative rates of nucleotide substitution; GTR+Γ: six rates and one Γ shape parameter) were randomly drawn from 142 sets of parameters derived from real-case data (see file <a href="https://zenodo.org/record/4034261/files/GTR.params.trees.tsv?download=1">GTR.params.trees.tsv</a> at <a href="https://zenodo.org/record/4034261">https://zenodo.org/record/4034261</a>). Initial sequence length was 5 Mbs, and an indel rate of 0.01 was set with indel length drawn from [1, 50000] according to a Zipf distribution with parameter 1.5 (see INDELible <a href="http://abacus.gene.ucl.ac.uk/software/indelible/manual/model.shtml">manual</a>).   For each of the 20 evolutionary distances d = 0.05, 0.10, ..., 1.00, six XZ-compressed files containing 200 simulation data are available: <ul> <li><code>data-d-f1-nogam.tsv.xz</code>   data simulated under the model GTR with equilibrium frequencies f1</li> <li><code>data-d-f1-gamma.tsv.xz</code>   data simulated under the model GTR+Γ with equilibrium frequencies f1</li> <li><code>data-d-f2-nogam.tsv.xz</code>   data simulated under the model GTR with equilibrium frequencies f2</li> <li><code>data-d-f2-gamma.tsv.xz</code>   data simulated under the model GTR+Γ with equilibrium frequencies f2</li> <li><code>data-d-f3-nogam.tsv.xz</code>   data simulated under the model GTR with equilibrium frequencies f3</li> <li><code>data-d-f3-gamma.tsv.xz</code>   data simulated under the model GTR+Γ with equilibrium frequencies f3</li> </ul>   Each file is tab-delimited and contains the 18 following fields: <ul> <li><code>[1]   </code>   integer seed value specified to INDELible,</li> <li><code>[2-5] </code>   frequencies of T, C, A, G, respectively, specified to INDELible,</li> <li><code>[6-10] </code> C-T, A-T, G-T, A-C, C-G rate parameters, respectivly (normalized such that A-G rate = 1), specified to INDELible,</li> <li><code>[11]   </code>   Γ shape parameter alpha (= 0 in the <code>nogam</code> files, i.e. GTR substitution model without Γ) specified to INDELible,</li> <li><code>[12]   </code>   length lgt1 of the first sequence seq1 (i.e. no. A, C, G, T in seq1),</li> <li><code>[13]   </code>   length lgt2 of the second sequence seq2 (i.e. no. A, C, G, T in seq2),</li> <li><code>[14]   </code>   no. sites in aligned sequences seq1 and seq2 (i.e. no. A, C, G, T and gap character states in seq1 or seq2),</li> <li><code>[15]   </code>   no. non-gapped sites (core sites) in aligned sequences seq1 and seq2,</li> <li><code>[16]   </code>   observed p-distance between aligned sequences seq1 and seq2 (i.e. no. nucleotide mismatches divided by no. core sites),</li> <li><code>[17]   </code>   aligned seq1 (containing indel gaps),</li> <li><code>[18]   </code>   aligned seq2 (containing indel gaps).</li> </ul> Of note, seq1 and seq2 (fields <code>[17-18]</code>) being aligned, these two entries are two strings with identical no. sites (field <code>[14]</code>). Gap character states (<code>-</code>) should be removed from seq1 and seq2 to obtain the unaligned sequences. _____ Criscuolo A (2020) On the transformation of MinHash-based uncorrected distances into proper evolutionary distances for phylogenetic inference. F1000Research, 9:1309. <a href="https://doi.org/10.12688/f1000research.26930.1">doi:10.12688/f1000research.26930.1</a>

opencc-by-4.0Dec 2020View details →

Alignment used for the phylogenies of "The earliest diverging extant scleractinian corals recovered by mitochondrial genomes"

Alignment of scleractinian corals based on mitochondrial genomes and including species of the family Micrabaciidae. This alignment was used for running Maximum Likelihood and Bayesian Inference phylogenies. "tree02_alignment.phy" refers to the actual alignment while "tree02_alignment.partitions.txt" indicates where each gene partition begins/ends.

opencc-zeroDec 2017View details →

Data from: Reconstructing phylogeny from reduced-representation genome sequencing data without assembly or alignment

Reduced-representation genome sequencing such as RADseq aids the analysis of genomes by reducing the quantity of data, thereby lowering both sequencing costs and computational burdens. RADseq was initially designed for studying genetic variation across genomes at the population level, but has also proved to be suitable for interspecific phylogeny reconstruction. RADseq data pose challenges for standard phylogenomic methods, however, due to incomplete coverage of the genome and large amounts of missing data. Alignment-free methods are both efficient and accurate for phylogenetic reconstructions with whole genomes and are especially practical for non-model organisms; nonetheless, alignment-free methods have not been applied with reduced genome sequencing data. Here, we test a full-genome assembly and alignment-free method, AAF, in application to RADseq data and propose two procedures for reads selection to remove reads from restriction sites that were not found in taxa being compared. We validate these methods using both simulations and real datasets. Reads selection improved the accuracy of phylogenetic construction in every simulated scenario and the two real datasets, making AAF as good or better than a comparable alignment-based method, even though AAF had much lower computational burdens. We also investigated the sources of missing data in RADseq and their effects on phylogeny reconstruction using AAF. The AAF pipeline modified for RADseq or other reduced-representation sequencing data, phyloRAD, is available on github (https://github.com/fanhuan/phyloRAD).

opencc-zeroOct 2023View details →

MtDNA genomes from Ranis individuals aligned with previously published ancient & modern humans

The Middle to Upper Palaeolithic transition in Europe is associated with the regional disappearance of Neanderthals and the spread of Homo sapiens. Archaeological evidence indicates the presence of technocomplexes at the interface of this transition, complicating our understanding of the period and the association of those with specific hominin groups. One such technocomplex where the maker is unknown is the Lincombian-Ranisian-Jerzmanowician (LRJ), which covers an area in northwestern and central Europe from the UK to Poland. This paper presents the morphological and proteomic species identification, mitochondrial DNA analysis, and direct radiocarbon dating of human remains directly associated to an LRJ assemblage at the cave site of Ilsenhöhle in Ranis (Germany).

opencc-by-4.0Jun 2024View details →

Multiple whole genome alignment of 63 Nymphalidae (HAL file, alignment version 1.0), plus protein-coding annotations for each of the species in the hall file.

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openOct 2017View details →

Transcriptome profiling of derived-hepatocyte progenitors from human iPSCs with nanoCAGE - part1 - genomic alignments (hg19 + hg38)

This repository contains genomic alignments (BED files) of paired-end nanoCAGE sequencing data (CAGEscan data) collected from Illumina MiSeq run IDs "170630_M00528_0292_000000000-B9JY8" (aka "NC_LIMMS") and "180221_M00528_0334_000000000-B6PJM" (aka "NC_LIMMS2"). FASTQ files were processed with the MOIRAI pipeline OP-WORKFLOW-CAGEscan-short-reads-v2.1 (Hasegawa et al. BMC Bioinformatics 2014 May 16;15:144. doi: 10.1186/1471-2105-15-144.). Filtered pairs of reads were aligned on the human genome assemblies hg19 and hg38. See tables below for a detailed description of the samples contained in each nanoCAGE library, including barcodes and index sequences used for the demultiplexing of sequencing reads. Corresponding raw sequencing data files (FASTQ files) were deposited at Zenodo under the following Digital Object Identifier: 10.5281/zenodo.1014009.   "170630_M00528_0292_000000000-B9JY8" ("NC_LIMMS") : ID   Sample_name   Barcode_number   Barcode_sequence   Index_sequence 1   iPSC_control_rep1   4   ACAGAT   NNNNNNNN 2   iPSC_control_rep2   24   ATCGTG   NNNNNNNN 3   iPSC_control_rep3   31   CACGAT   NNNNNNNN 4   S3P1_OK_rep1   36   CACTGA   NNNNNNNN 5   S3P1_OK_rep2   46   CTGACG   NNNNNNNN 6   S3P1_OK_rep3   63   GAGTGA   NNNNNNNN 7   S4P1_OK_rep1   79   GTATAC   NNNNNNNN 8   S4P1_OK_rep2   92   TCGAGC   NNNNNNNN 9   S4P1_OK_rep3   9   ACATGA   NNNNNNNN 10   S4P2_OK_rep1   21   ATCATA   NNNNNNNN 11   S4P2_OK_rep2   33   CACGTG   NNNNNNNN 12   S4P2_OK_rep3   45   CGATGA   NNNNNNNN 13   S1P1_rep1   57   GAGATA   NNNNNNNN 14   S1P1_rep2   69   GCTCTC   NNNNNNNN 15   S1P1_rep3   81   GTATGA   NNNNNNNN 16   S3P1_FAILED_rep1   93   TCGATA   NNNNNNNN 17   S3P1_FAILED_rep2   11   AGTAGC   NNNNNNNN 18   S3P1_FAILED_rep3   23   ATCGCA   NNNNNNNN 19   S4P1_FAILED_rep1   35   CACTCT   NNNNNNNN 20   S4P1_FAILED_rep2   47   CTGAGC   NNNNNNNN 21   S4P1_FAILED_rep3   59   GAGCGT   NNNNNNNN 22   S4P2_FAILED_rep1   71   GCTGCA   NNNNNNNN 23   S4P2_FAILED_rep2   83   TATAGC   NNNNNNNN 24   S4P2_FAILED_rep3   95   TCGCGT   NNNNNNNN   "180221_M00528_0334_000000000-B6PJM" ("NC_LIMMS2"): ID   Sample_name   Barcode_number   Barcode_sequence   Index_sequence 25   PETRI_rep1   04   ACAGAT   NNNNNNNN 26   PETRI_rep2   24   ATCGTG   NNNNNNNN 27   PETRI_rep3   31   CACGAT   NNNNNNNN 28   BIOCHIP_E_rep1   6   CACTGA   NNNNNNNN 29   BIOCHIP_M_rep1   46   CTGACG   NNNNNNNN 30   BIOCHIP_S_rep1   63   GAGTGA   NNNNNNNN 31   BIOCHIP_E_rep2   79   GTATAC   NNNNNNNN 32   BIOCHIP_M_rep2   92   TCGAGC   NNNNNNNN 33   BIOCHIP_S_rep2   09   ACATGA   NNNNNNNN 34   BIOCHIP_E_rep3   21   ATCATA   NNNNNNNN 35   BIOCHIP_M_rep3   33   CACGTG   NNNNNNNN 36   BIOCHIP_S_rep3   45   CGATGA   NNNNNNNN 37   HEPATOCYTES_rep1   57   GAGATA   NNNNNNNN 38   HEPATOCYTES_rep2   69   GCTCTC   NNNNNNNN 39   iPSC_control_rep1-2   81   GTATGA   NNNNNNNN 40   BIOCHIP_E_rep2-2   93   TCGATA   NNNNNNNN 41   BIOCHIP_M_rep1-2    11   AGTAGC   NNNNNNNN 42   BIOCHIP_S_rep2-2   23   ATCGCA   NNNNNNNN

opencc-by-4.0Mar 2023View details →

genome alignment of 88 speceis

genome alignment of 88 speceis

opencc-zeroMar 2023View details →

VCF of structural variant calls of Nanopore data aligned to dm6 reference genome

Heterozygous chromosome inversions suppress meiotic crossover (CO) formation within an inversion, potentially because they lead to gross chromosome rearrangements that produce inviable gametes. Interestingly, COs are also severely reduced in regions nearby but outside of inversion breakpoints even though COs in these regions do not result in rearrangements. Our mechanistic understanding of why COs are suppressed outside of inversion breakpoints is limited by a lack of data on the frequency of noncrossover gene conversions (NCOGCs) in these regions. To address this critical gap, we mapped the location and frequency of rare CO and NCOGC events that occurred outside of the dl-49 chrX inversion in D. melanogaster. We created full-sibling wildtype and inversion stocks and recovered COs and NCOGCs in the syntenic regions of both stocks, allowing us to directly compare rates and distributions of recombination events. We show that COs are completely suppressed within 500 kb of inversion breakpoints, are severely reduced within 2 Mb of an inversion breakpoint, and increase above wildtype levels 2–4 Mb from the breakpoint. We find that NCOGCs occur evenly throughout the chromosome and, importantly, occur at wild-type levels near inversion breakpoints. We propose a model in which COs are suppressed by inversion breakpoints in a distance-dependent manner through mechanisms that influence DNA double-strand break repair outcome but not double-strand break location or frequency. We suggest that subtle changes in the synaptonemal complex and chromosome pairing might lead to unstable interhomolog interactions during recombination that permits NCOGC formation but not CO formation.

publicOct 2023View details →

MtDNA genomes from Ranis individuals aligned with previously published ancient & modern humans

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publicMay 2018View details →

Data from: Reconstructing phylogeny from reduced-representation genome sequencing data without assembly or alignment

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