Screening synteny blocks in pairwise genome comparisons through integer programming

<p>Abstract</p> <p>Background</p> <p>It is difficult to accurately interpret chromosomal correspondences such as true orthology and paralogy due to significant divergence of genomes from a common ancestor. Analyses are particularly problematic among lineages that have repeatedly experienced whole genome duplication (WGD) events. To compare multiple "subgenomes" derived from genome duplications, we need to relax the traditional requirements of "one-to-one" syntenic matchings of genomic regions in order to reflect "one-to-many" or more generally "many-to-many" matchings. However this relaxation may result in the identification of synteny blocks that are derived from ancient shared WGDs that are not of interest. For many downstream analyses, we need to eliminate weak, low scoring alignments from pairwise genome comparisons. Our goal is to objectively select subset of synteny blocks whose total scores are maximized while respecting the duplication history of the genomes in comparison. We call this "quota-based" screening of synteny blocks in order to appropriately fill a quota of syntenic relationships within one genome or between two genomes having WGD events.</p> <p>Results</p> <p>We have formulated the synteny block screening as an optimization problem known as "Binary Integer Programming" (BIP), which is solved using existing linear programming solvers. The computer program QUOTA-ALIGN performs this task by creating a clear objective function that maximizes the compatible set of synteny blocks under given constraints on overlaps and depths (corresponding to the duplication history in respective genomes). Such a procedure is useful for any pairwise synteny alignments, but is most useful in lineages affected by multiple WGDs, like plants or fish lineages. For example, there should be a 1:2 ploidy relationship between genome A and B if genome B had an independent WGD subsequent to the divergence of the two genomes. We show through simulations and real examples using plant genomes in the rosid superorder that the quota-based screening can eliminate ambiguous synteny blocks and focus on specific genomic evolutionary events, like the divergence of lineages (in cross-species comparisons) and the most recent WGD (in self comparisons).</p> <p>Conclusions</p> <p>The QUOTA-ALIGN algorithm screens a set of synteny blocks to retain only those compatible with a user specified ploidy relationship between two genomes. These blocks, in turn, may be used for additional downstream analyses such as identifying true orthologous regions in interspecific comparisons. There are two major contributions of QUOTA-ALIGN: 1) reducing the block screening task to a BIP problem, which is novel; 2) providing an efficient software pipeline starting from all-against-all BLAST to the screened synteny blocks with dot plot visualizations. Python codes and full documentations are publicly available <url>http://github.com/tanghaibao/quota-alignment</url>. QUOTA-ALIGN program is also integrated as a major component in SynMap <url>http://genomevolution.com/CoGe/SynMap.pl</url>, offering easier access to thousands of genomes for non-programmers.</p

SynFind: Compiling Syntenic Regions across Any Set of Genomes on Demand

The identification of conserved syntenic regions enables discovery of predicted locations for orthologous and homeologous genes, evenwhennosuchgeneispresent.Thiscapabilitymeansthatsynteny-basedmethodsarefarmoreeffectivethansequencesimilaritybased methods in identifying true-negatives, a necessity forstudying gene loss and gene transposition. However, the identification of syntenicregionsrequirescomplexanalyseswhichmustberepeatedforpairwisecomparisonsbetweenanytwospecies.Therefore,as the number of published genomes increases, there is a growing demand for scalable, simple-to-use applications to perform comparative genomic analyses that cater to both gene family studies and genome-scale studies. We implemented SynFind, a web-based tool that addresses this need. Given one query genome, SynFind is capable of identifying conserved syntenic regions in any set of targetgenomes.SynFindiscapableofreportingper-geneinformation,usefulforresearchersstudyingspecificgenefamilies,aswellas genome-wide data sets of syntenic gene and predicted gene locations, critical for researchers focused on large-scale genomic analyses. Inference of syntenic homologs provides the basis for correlation of functional changes around genes of interests between related organisms. Deployed on the CoGe online platform, SynFind is connected to the genomic data from over 15,000 organisms from all domains of life as well as supporting multiple releases of the same organism. SynFind makes use of a powerful job execution framework that promises scalability and reproducibility. SynFind can be accessed at http://genomevolution.org/CoGe/SynFind.pl. A video tutorial of SynFind using Phytophthrora as an example is available at http://www.youtube.com/watch?v=2Agczny9Nyc

SynFind: Compiling Syntenic Regions across Any Set of Genomes on Demand

The identification of conserved syntenic regions enables discovery of predicted locations for orthologous and homeologous genes, evenwhennosuchgeneispresent.Thiscapabilitymeansthatsynteny-basedmethodsarefarmoreeffectivethansequencesimilaritybased methods in identifying true-negatives, a necessity forstudying gene loss and gene transposition. However, the identification of syntenicregionsrequirescomplexanalyseswhichmustberepeatedforpairwisecomparisonsbetweenanytwospecies.Therefore,as the number of published genomes increases, there is a growing demand for scalable, simple-to-use applications to perform comparative genomic analyses that cater to both gene family studies and genome-scale studies. We implemented SynFind, a web-based tool that addresses this need. Given one query genome, SynFind is capable of identifying conserved syntenic regions in any set of targetgenomes.SynFindiscapableofreportingper-geneinformation,usefulforresearchersstudyingspecificgenefamilies,aswellas genome-wide data sets of syntenic gene and predicted gene locations, critical for researchers focused on large-scale genomic analyses. Inference of syntenic homologs provides the basis for correlation of functional changes around genes of interests between related organisms. Deployed on the CoGe online platform, SynFind is connected to the genomic data from over 15,000 organisms from all domains of life as well as supporting multiple releases of the same organism. SynFind makes use of a powerful job execution framework that promises scalability and reproducibility. SynFind can be accessed at http://genomevolution.org/CoGe/SynFind.pl. A video tutorial of SynFind using Phytophthrora as an example is available at http://www.youtube.com/watch?v=2Agczny9Nyc

Saturation of an Intra-Gene Pool Linkage Map: Towards a Unified Consensus Linkage Map for Fine Mapping and Synteny Analysis in Common Bean

Map-based cloning and fine mapping to find genes of interest and marker assisted selection (MAS) requires good genetic maps with reproducible markers. In this study, we saturated the linkage map of the intra-gene pool population of common bean DOR364×BAT477 (DB) by evaluating 2,706 molecular markers including SSR, SNP, and gene-based markers. On average the polymorphism rate was 7.7% due to the narrow genetic base between the parents. The DB linkage map consisted of 291 markers with a total map length of 1,788 cM. A consensus map was built using the core mapping populations derived from inter-gene pool crosses: DOR364×G19833 (DG) and BAT93×JALO EEP558 (BJ). The consensus map consisted of a total of 1,010 markers mapped, with a total map length of 2,041 cM across 11 linkage groups. On average, each linkage group on the consensus map contained 91 markers of which 83% were single copy markers. Finally, a synteny analysis was carried out using our highly saturated consensus maps compared with the soybean pseudo-chromosome assembly. A total of 772 marker sequences were compared with the soybean genome. A total of 44 syntenic blocks were identified. The linkage group Pv6 presented the most diverse pattern of synteny with seven syntenic blocks, and Pv9 showed the most consistent relations with soybean with just two syntenic blocks. Additionally, a co-linear analysis using common bean transcript map information against soybean coding sequences (CDS) revealed the relationship with 787 soybean genes. The common bean consensus map has allowed us to map a larger number of markers, to obtain a more complete coverage of the common bean genome. Our results, combined with synteny relationships provide tools to increase marker density in selected genomic regions to identify closely linked polymorphic markers for indirect selection, fine mapping or for positional cloning

Genome-Wide Analysis of Syntenic Gene Deletion in the Grasses

The grasses, Poaceae, are one of the largest and most successful angiosperm families. Like many radiations of flowering plants, the divergence of the major grass lineages was preceded by a whole-genome duplication (WGD), although these events are not rare for flowering plants. By combining identification of syntenic gene blocks with measures of gene pair divergence and different frequencies of ancient gene loss, we have separated the two subgenomes present in modern grasses. Reciprocal loss of duplicated genes or genomic regions has been hypothesized to reproductively isolate populations and, thus, speciation. However, in contrast to previous studies in yeast and teleost fishes, we found very little evidence of reciprocal loss of homeologous genes between the grasses, suggesting that post-WGD gene loss may not be the cause of the grass radiation. The sets of homeologous and orthologous genes and predicted locations of deleted genes identified in this study, as well as links to the CoGe comparative genomics web platform for analyzing pan-grass syntenic regions, are provided along with this paper as a resource for the grass genetics community

i-ADHoRe 3.0—fast and sensitive detection of genomic homology in extremely large data sets

Comparative genomics is a powerful means to gain insight into the evolutionary processes that shape the genomes of related species. As the number of sequenced genomes increases, the development of software to perform accurate cross-species analyses becomes indispensable. However, many implementations that have the ability to compare multiple genomes exhibit unfavorable computational and memory requirements, limiting the number of genomes that can be analyzed in one run. Here, we present a software package to unveil genomic homology based on the identification of conservation of gene content and gene order (collinearity), i-ADHoRe 3.0, and its application to eukaryotic genomes. The use of efficient algorithms and support for parallel computing enable the analysis of large-scale data sets. Unlike other tools, i-ADHoRe can process the Ensembl data set, containing 49 species, in 1 h. Furthermore, the profile search is more sensitive to detect degenerate genomic homology than chaining pairwise collinearity information based on transitive homology. From ultra-conserved collinear regions between mammals and birds, by integrating coexpression information and protein–protein interactions, we identified more than 400 regions in the human genome showing significant functional coherence. The different algorithmical improvements ensure that i-ADHoRe 3.0 will remain a powerful tool to study genome evolution

A novel approach for multi-domain and multi-gene famliy identification provides insights into evolutionary dynamics of disease resistance genes in core eudicot plants

Background Recent advances in DNA sequencing techniques resulted in more than forty sequenced plant genomes representing a diverse set of taxa of agricultural, energy, medicinal and ecological importance. However, gene family curation is often only inferred from DNA sequence homology and lacks insights into evolutionary processes contributing to gene family dynamics. In a comparative genomics framework, we integrated multiple lines of evidence provided by gene synteny, sequence homology and protein-based Hidden Markov Modelling to extract homologous super-clusters composed of multi-domain resistance (R)-proteins of the NB-LRR type (for NUCLEOTIDE BINDING/LEUCINE-RICH REPEATS), that are involved in plant innate immunity. Results To assess the diversity of R-proteins within and between species, we screened twelve eudicot plant genomes including six major crops and found a total of 2,363 NB-LRR genes. Our curated R-proteins set shows a 50% average for tandem duplicates and a 22% fraction of gene copies retained from ancient polyploidy events (ohnologs). We provide evidence for strong positive selection acting on all identified genes and show significant differences in molecular evolution rates (Ka/Ks-ratio) among tandem- (mean = 1.59), ohnolog (mean = 1.36) and singleton (mean = 1.22) R-gene duplicates. To foster the process of gene-edited plant breeding, we report species-specific presence/absence of all 140 NB-LRR genes present in the model plant Arabidopsis and describe four distinct clusters of NB-LRR "gatekeeper" loci sharing syntenic orthologs across all analyzed genomes. Conclusion By curating a near-complete set of multi-domain R-protein clusters in an eudicot-wide scale, our analysis offers significant insight into evolutionary dynamics underlying diversification of the plant innate immune system. Furthermore, our methods provide a blueprint for future efforts to identify and more rapidly clone functional NB-LRR genes from any plant species

Genome sequence and evolution of Betula platyphylla

Betula L. (birch) is a pioneer hardwood tree species with ecological, economic, and evolutionary importance in the Northern Hemisphere. We sequenced the Betula platyphylla genome and assembled the sequences into 14 chromosomes. The Betula genome lacks evidence of recent whole-genome duplication and has the same paleoploidy level as Vitis vinifera and Prunus mume. Phylogenetic analysis of lignin pathway genes coupled with tissue-specific expression patterns provided clues for understanding the formation of higher ratios of syringyl to guaiacyl lignin observed in Betula species. Our transcriptome analysis of leaf tissues under a time-series cold stress experiment revealed the presence of the MEKK1–MKK2–MPK4 cascade and six additional mitogen-activated protein kinases that can be linked to a gene regulatory network involving many transcription factors and cold tolerance genes. Our genomic and transcriptome analyses provide insight into the structures, features, and evolution of the B. platyphylla genome. The chromosome-level genome and gene resources of B. platyphylla obtained in this study will facilitate the identification of important and essential genes governing important traits of trees and genetic improvement of B. platyphylla

Origin and evolution of the octoploid strawberry genome.

Cultivated strawberry emerged from the hybridization of two wild octoploid species, both descendants from the merger of four diploid progenitor species into a single nucleus more than 1 million years ago. Here we report a near-complete chromosome-scale assembly for cultivated octoploid strawberry (Fragaria × ananassa) and uncovered the origin and evolutionary processes that shaped this complex allopolyploid. We identified the extant relatives of each diploid progenitor species and provide support for the North American origin of octoploid strawberry. We examined the dynamics among the four subgenomes in octoploid strawberry and uncovered the presence of a single dominant subgenome with significantly greater gene content, gene expression abundance, and biased exchanges between homoeologous chromosomes, as compared with the other subgenomes. Pathway analysis showed that certain metabolomic and disease-resistance traits are largely controlled by the dominant subgenome. These findings and the reference genome should serve as a powerful platform for future evolutionary studies and enable molecular breeding in strawberry

Extensive gene content variation in the <i>Brachypodium distachyon</i> pan-genome correlates with population structure

13 Pags.- 6 Figs. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holderWhile prokaryotic pan-genomes have been shown to contain many more genes than any individual organism, the prevalence and functional significance of differentially present genes in eukaryotes remains poorly understood. Whole-genome de novo assembly and annotation of 54 lines of the grass Brachypodium distachyon yield a pan-genome containing nearly twice the number of genes found in any individual genome. Genes present in all lines are enriched for essential biological functions, while genes present in only some lines are enriched for conditionally beneficial functions (e.g., defense and development), display faster evolutionary rates, lie closer to transposable elements and are less likely to be syntenic with orthologous genes in other grasses. Our data suggest that differentially present genes contribute substantially to phenotypic variation within a eukaryote species, these genes have a major influence in population genetics, and transposable elements play a key role in pan-genome evolution.The work conducted by the US DOE Joint Genome Institute is supported by the Office of Science of the US Department of Energy under Contract no. DE-AC02-05CH11231. D.P. W. and R.A. were funded in part by the National Science Foundation (grant no. IOS–1258126), and the Great Lakes Bioenergy Research Center (Department of Energy Biological and Environmental Research Office of Science grant no. DE– FCO2–07ER64494). TEJ and DLDM were supported by NSF PGRP grant IOS-0922457. P.C. and B.C.M. were funded by Spanish MINECO (CGL2012-39953-C02-01 and CGL2016-79790-P). B.C.M. was partially funded by DGA—Obra Social La Caixa (grant number GA-LC-059-2011) and Spanish MINECO (AGL2013-48756-R, CSIC13-4E-2490). PC was partially funded by Spanish Aragon Government-European Social Fund (Bioflora).Peer reviewe