Highly evolvable malaria vectors: The genomes of 16
            <i>Anopheles</i>
            mosquitoes

Neafsey, Daniel E.; Waterhouse, Robert M.; Abai, Mohammad Reza; Aganezov, Sergey; Alekseyev, Max A.; Allen, James; Amon, James; Arcà, Bruno; Arensburger, Peter; Artemov, Gleb N.; Assour, Lauren A.; Basseri, Hamid Reza; Berlin, Aaron M.; Birren, Bruce W.; Blandin, Stéphanie; Brockman, Andrew I.; Burkot, Thomas R.; Burt, Austin; Chan, Clara S.; Chauve, Cédric; Chiu, Joanna C.; Christensen, Mikkel; Costantini, Carlo; Davidson, Victoria L M; Deligianni, Elena; Dottorini, Tania; Dritsou, Vicky; Gabriel, Stacey; Guelbeogo, Wamdaogo M.; Hall, Andrew Brantley; Han, Mira V.; Hlaing, Thaung; Hughes, Daniel; Jenkins, Adam M.; Jiang, Xiaofang; Jungreis, Irwin; Kakani, Evdoxia G.; Kamali, Maryam; Kemppainen, Petri; Kennedy, Ryan; Kirmitzoglou, Ioannis; Koekemoer, Lizette L.; Njoroge, Laban; Langridge, Nicholas; Lawniczak, Mara; Lirakis, Manolis; Lobo, Neil F.; Lowy, Ernesto; MacCallum, Robert M.; Mao, Chunhong; Maslen, G.; Mbogo, Charles M.; McCarthy, Jenny; Michel, Kristin; Mitchell, Sara N.; Moore, Wendy; Murphy, Katherine A.; Naumenko, Anastasia N.; Nolan, Tony; Novoa, Eva María; OʼLoughlin, Samantha; Oringanje, Chioma; Oshaghi, Mohammad Ali; Pakpour, Nazzy; Papathanos, Philippos Aris; Peery, Ashley; Povelones, Michael; Prakash, Anil; Price, David; Rajaraman, Ashok; Reimer, Lisa J.; Rinker, David C.; Rokas, Antonis; Russell, Tanya L.; Sagnon, N’Falé; Sharakhov, Igor V.; Shea, Terrance; Simão, Felipe A.; Simard, Frédéric; Slotman, Michel A.; Somboon, Pradya; Stegniy, V. N.; Struchiner, Cláudio J.; Thomas, Gregg W.C.; Tojo, Marta; Topalis, Pantelis; Tubío, José M. C.; Unger, Maria; Vontas, John; Walton, Catherine; Wilding, Craig S.; Willis, Judith H.; Wu, Yi; Yan, Guiyun; Zdobnov, Evgeny M.; Zhou, Xiaofan; Catteruccia, Flaminia; Christophides, George K.; Collins, Frank H.; Cornman, Robert S.; Crisanti, Andrea; Donnelly, Martin J.; Emrich, Scott J.; Fontaine, Michaël C.; Gelbart, William M.; Hahn, Matthew W.; Hansen, Immo A.; Howell, Paul; Kafatos, Fotis C.; Kellis, M; Lawson, Daniel; Louis, Christos; Luckhart, Shirley; Muskavitch, Marc A. T.; Ribeiro, José M. C.; Riehle, Michael A.; Tu, Zhijian; Zwiebel, Laurence J.; Besansky, Nora J.

doi:10.1126/science.1258522

Cited by 539 publications

(721 citation statements)

References 240 publications

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“…In contrast, multiple de novo assemblies of pig genomes from different regions and breeds promise a more accurate and comprehensive understanding of genetic variation within this species (Besenbacher et al 2015;Chaisson et al 2015b). Among populations of plants (coccolithophores [Read et al 2013], Arabidopsis thaliana [Gan et al 2011], soybean , and rice ), animals (mosquitoes [Neafsey et al 2015] and macaques [Yan et al 2011]), and even modern humans (Li et al 2010a), a surprisingly large amount of variation has been uncovered by de novo assemblies.…”

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confidence: 99%

Comprehensive variation discovery and recovery of missing sequence in the pig genome using multiple de novo assemblies

et al. 2016

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Uncovering genetic variation through resequencing is limited by the fact that only sequences with similarity to the reference genome are examined. Reference genomes are often incomplete and cannot represent the full range of genetic diversity as a result of geographical divergence and independent demographic events. To more comprehensively characterize genetic variation of pigs (Sus scrofa), we generated de novo assemblies of nine geographically and phenotypically representative pigs from Eurasia. By comparing them to the reference pig assembly, we uncovered a substantial number of novel SNPs and structural variants, as well as 137.02-Mb sequences harboring 1737 protein-coding genes that were absent in the reference assembly, revealing variants left by selection. Our results illustrate the power of whole-genome de novo sequencing relative to resequencing and provide valuable genetic resources that enable effective use of pigs in both agricultural production and biomedical research.

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confidence: 99%

Comprehensive variation discovery and recovery of missing sequence in the pig genome using multiple de novo assemblies

et al. 2016

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“…CAMSA is currently utilized in the study of Anopheles mosquito genomes [46], where multiple research laboratories work on improving the existing assemblies for a set of mosquito species. 1 We remark that contigs can be viewed as scaffolds with no gaps.…”

Section: Resultsmentioning

confidence: 99%

CAMSA: A tool for comparative analysis and merging of scaffold assemblies

Aganezov

Alekseyev

2016

2016 IEEE 6th International Conference on Computational Advances in Bio and Medical Sciences (ICCABS)

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Background: Despite the recent progress in genome sequencing and assembly, many of the currently available assembled genomes come in a draft form. Such draft genomes consist of a large number of genomic fragments (scaffolds), whose positions and orientations along the genome are unknown. While there exists a number of methods for reconstruction of the genome from its scaffolds, utilizing various computational and wet-lab techniques, they often can produce only partial error-prone scaffold assemblies. It therefore becomes important to compare and merge scaffold assemblies produced by different methods, thus combining their advantages and highlighting present conflicts for further investigation. These tasks may be labor intensive if performed manually. Results: We present CAMSA-a tool for comparative analysis and merging of two or more given scaffold assemblies. The tool (i) creates an extensive report with several comparative quality metrics; (ii) constructs the most confident merged scaffold assembly; and (iii) provides an interactive framework for a visual comparative analysis of the given assemblies. Among the CAMSA features, only scaffold merging can be evaluated in comparison to existing methods. Namely, it resembles the functionality of assembly reconciliation tools, although their primary targets are somewhat different. Our evaluations show that CAMSA produces merged assemblies of comparable or better quality than existing assembly reconciliation tools while being the fastest in terms of the total running time. Conclusions: CAMSA addresses the current deficiency of tools for automated comparison and analysis of multiple assemblies of the same set scaffolds. Since there exist numerous methods and techniques for scaffold assembly, identifying similarities and dissimilarities across assemblies produced by different methods is beneficial both for the developers of scaffold assembly algorithms and for the researchers focused on improving draft assemblies of specific organisms.

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“…Our empirical study included a re-analysis of a phylogenomic dataset from the study of Neafsey et al [46]. We obtained the original ver- across sites [49].…”

Section: Empirical Datasetsmentioning

confidence: 99%

Fast and accurate statistical inference of phylogenetic networks using large-scale genomic sequence data

Hejase

Vandepol

Bonito

et al. 2017

Preprint

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An emerging discovery in phylogenomics is that interspecific gene flow has played a major role in the evolution of many different organisms. To what extent is the Tree of Life not truly a tree reflecting strict “vertical” divergence, but rather a more general graph structure known as a phylogenetic network which also captures “horizontal”gene flow? The answer to this fundamental question not only depends upon densely sampled and divergent genomic sequence data, but also compu-tational methods which are capable of accurately and efficiently inferring phylogenetic networks from large-scale genomic sequence datasets. Re-cent methodological advances have attempted to address this gap. How-ever, in the 2016 performance study of Hejase and Liu, state-of-the-art methods fell well short of the scalability requirements of existing phy-logenomic studies.The methodological gap remains: how can phylogenetic networks be ac-curately and efficiently inferred using genomic sequence data involving many dozens or hundreds of taxa? In this study, we address this gap by proposing a new phylogenetic divide-and-conquer method which we call FastNet. We conduct a performance study involving a range of evolu-tionary scenarios, and we demonstrate that FastNet outperforms state-of-the-art methods in terms of computational efficiency and topological accuracy.

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Highly evolvable malaria vectors: The genomes of 16 Anopheles mosquitoes

Cited by 539 publications

References 240 publications

Comprehensive variation discovery and recovery of missing sequence in the pig genome using multiple de novo assemblies

Comprehensive variation discovery and recovery of missing sequence in the pig genome using multiple de novo assemblies

CAMSA: A tool for comparative analysis and merging of scaffold assemblies

Fast and accurate statistical inference of phylogenetic networks using large-scale genomic sequence data

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