Liliana M. Dávalos

Bio: Liliana M. Dávalos is an academic researcher from Stony Brook University. The author has contributed to research in topics: Genome & Medicine. The author has an hindex of 29, co-authored 95 publications receiving 3123 citations. Previous affiliations of Liliana M. Dávalos include Open University & National University of Colombia.

Geographical sampling bias and its implications for conservation priorities in Africa

Abstract: Aim To design and apply statistical tests for measuring sampling bias in the raw data used to the determine priority areas for conservation, and to discuss their impact on conservation analyses for the region. LocationSub-Saharan Africa. Methods An extensive data set comprising 78,083 vouchered locality records for 1068 passerine birds in sub-Saharan Africa has been assembled. Using geographical information systems, we designed and applied two tests to determine if sampling of these taxa was biased. First, we detected possible biases because of accessibility by measuring the proximity of each record to cities, rivers and roads. Second, we quantified the intensity of sampling of each species inside and surrounding proposed conservation priority areas and compared it with sampling intensity in non-priority areas. We applied statistical tests to determine if the distribution of these sampling records deviated significantly from random distributions. Results The analyses show that the location and intensity of collecting have historically been heavily influenced by accessibility. Sampling localities show dense, significant aggregation around city limits, and along rivers and roads. When examining the collecting sites of each individual species, the pattern of sampling has been significantly concentrated within and immediately surrounding areas now designated as conservation priorities. Main conclusions Assessment of patterns of species richness and endemicity at the scale useful for establishing conservation priorities, below the continental level, undoubtedly reflects biases in taxonomic sampling. This is especially problematic for priorities established using the criterion of complementarity because the estimated spatial costs of this approach are highly sensitive to sampling artefacts. Hence such conservation priorities should be interpreted with caution proportional to the bias found. We argue that conservation priority setting analyses require (1) statistical tests to detect these biases, and (2) data treatment to reflect species distribution rather than patterns of collecting effort.

The nature and dynamics of bacterial genomes.

Abstract: Though generally small and gene rich, bacterial genomes are constantly subjected to both mutational and population-level processes that operate to increase amounts of functionless DNA. As a result, the coding potential of bacterial genomes can be substantially lower than originally predicted. Whereas only a single pseudogene was included in the original annotation of the bacterium Escherichia coli, we estimate that this genome harbors hundreds of inactivated and otherwise functionless genes. Such regions will never yield a detectable phenotype, but their identification is vital to efforts to elucidate the biological role of all the proteins within the cell.

Morphological innovation, diversification and invasion of a new adaptive zone

Abstract: How ecological opportunity relates to diversification is a central question in evolutionary biology. However, there are few empirical examples of how ecological opportunity and morphological innovation open new adaptive zones, and promote diversification. We analyse data on diet, skull morphology and bite performance, and relate these traits to diversification rates throughout the evolutionary history of an ecologically diverse family of mammals (Chiroptera: Phyllostomidae). We found a significant increase in diversification rate driven by increased speciation at the most recent common ancestor of the predominantly frugivorous subfamily Stenodermatinae. The evolution of diet was associated with skull morphology, and morphology was tightly coupled with biting performance, linking phenotype to new niches through performance. Following the increase in speciation rate, the rate of morphological evolution slowed, while the rate of evolution in diet increased. This pattern suggests that morphology stabilized, and niches within the new adaptive zone of frugivory were filled rapidly, after the evolution of a new cranial phenotype that resulted in a certain level of mechanical efficiency. The tree-wide speciation rate increased non linearly with a more frugivorous diet, and was highest at measures of skull morphology associated with morphological extremes, including the most derived Stenodermatines. These results show that a novel stenodermatine skull phenotype played a central role in the evolution of frugivory and increasing speciation within phyllostomids.

Six reference-quality genomes reveal evolution of bat adaptations

Abstract: Bats possess extraordinary adaptations, including flight, echolocation, extreme longevity and unique immunity. High-quality genomes are crucial for understanding the molecular basis and evolution of these traits. Here we incorporated long-read sequencing and state-of-the-art scaffolding protocols1 to generate, to our knowledge, the first reference-quality genomes of six bat species (Rhinolophus ferrumequinum, Rousettus aegyptiacus, Phyllostomus discolor, Myotis myotis, Pipistrellus kuhlii and Molossus molossus). We integrated gene projections from our ‘Tool to infer Orthologs from Genome Alignments’ (TOGA) software with de novo and homology gene predictions as well as short- and long-read transcriptomics to generate highly complete gene annotations. To resolve the phylogenetic position of bats within Laurasiatheria, we applied several phylogenetic methods to comprehensive sets of orthologous protein-coding and noncoding regions of the genome, and identified a basal origin for bats within Scrotifera. Our genome-wide screens revealed positive selection on hearing-related genes in the ancestral branch of bats, which is indicative of laryngeal echolocation being an ancestral trait in this clade. We found selection and loss of immunity-related genes (including pro-inflammatory NF-κB regulators) and expansions of anti-viral APOBEC3 genes, which highlights molecular mechanisms that may contribute to the exceptional immunity of bats. Genomic integrations of diverse viruses provide a genomic record of historical tolerance to viral infection in bats. Finally, we found and experimentally validated bat-specific variation in microRNAs, which may regulate bat-specific gene-expression programs. Our reference-quality bat genomes provide the resources required to uncover and validate the genomic basis of adaptations of bats, and stimulate new avenues of research that are directly relevant to human health and disease1. Reference-quality genomes for six bat species shed light on the phylogenetic position of Chiroptera, and provide insight into the genetic underpinnings of the unique adaptations of this clade.

Forests and Drugs: Coca-Driven Deforestation in Tropical Biodiversity Hotspots

Abstract: Identifying drivers of deforestation in tropical biodiversity hotspots is critical to assess threats to particular ecosystems and species and proactively plan for conservation. We analyzed land cover change between 2002 and 2007 in the northern Andes, Choco, and Amazon forests of Colombia, the largest producer of coca leaf for the global cocaine market, to quantify the impact of this illicit crop on forest dynamics, evaluate the effectiveness of protected areas in this context, and determine the effects of eradication on deforestation. Landscape-level analyses of forest conversion revealed that proximity to new coca plots and a greater proportion of an area planted with coca increased the probability of forest loss in southern Colombia, even after accounting for other covariates and spatial autocorrelation. We also showed that protected areas successfully reduced forest conversion in coca-growing regions. Neither eradication nor coca cultivation predicted deforestation rates across municipalities. Instead, the presence of new coca cultivation was an indicator of municipalities, where increasing population led to higher deforestation rates. We hypothesize that poor rural development underlies the relationship between population density and deforestation in coca-growing areas. Conservation in Colombia's vast forest frontier, which overlaps with its coca frontier, requires a mix of protected areas and strategic rural development to succeed.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

The Theory of Island Biogeography

Abstract: Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation

Abstract: Accurate modeling of geographic distributions of species is crucial to various applications in ecology and conservation. The best performing techniques often require some parameter tuning, which may be prohibitively time-consuming to do separately for each species, or unreliable for small or biased datasets. Additionally, even with the abundance of good quality data, users interested in the application of species models need not have the statistical knowledge required for detailed tuning. In such cases, it is desirable to use "default settings", tuned and validated on diverse datasets. Maxent is a recently introduced modeling technique, achieving high predictive accuracy and enjoying several additional attractive properties. The performance of Maxent is influenced by a moderate number of parameters. The first contribution of this paper is the empirical tuning of these parameters. Since many datasets lack information about species absence, we present a tuning method that uses presence-only data. We evaluate our method on independently collected high-quality presence-absence data. In addition to tuning, we introduce several concepts that improve the predictive accuracy and running time of Maxent. We introduce "hinge features" that model more complex relationships in the training data; we describe a new logistic output format that gives an estimate of probability of presence; finally we explore "background sampling" strategies that cope with sample selection bias and decrease model-building time. Our evaluation, based on a diverse dataset of 226 species from 6 regions, shows: 1) default settings tuned on presence-only data achieve performance which is almost as good as if they had been tuned on the evaluation data itself; 2) hinge features substantially improve model performance; 3) logistic output improves model calibration, so that large differences in output values correspond better to large differences in suitability; 4) "target-group" background sampling can give much better predictive performance than random background sampling; 5) random background sampling results in a dramatic decrease in running time, with no decrease in model performance.