mtDNAcombine: tools to combine sequences from multiple studies

Background Today an unprecedented amount of genetic sequence data is stored in publicly available repositories. For decades now, mitochondrial DNA (mtDNA) has been the workhorse of genetic studies, and as a result, there is a large volume of mtDNA data available in these repositories for a wide range of species. Indeed, whilst whole genome sequencing is an exciting prospect for the future, for most non-model organisms’ classical markers such as mtDNA remain widely used. By compiling existing data from multiple original studies, it is possible to build powerful new datasets capable of exploring many questions in ecology, evolution and conservation biology. One key question that these data can help inform is what happened in a species’ demographic past. However, compiling data in this manner is not trivial, there are many complexities associated with data extraction, data quality and data handling. Results Here we present the mtDNAcombine package, a collection of tools developed to manage some of the major decisions associated with handling multi-study sequence data with a particular focus on preparing sequence data for Bayesian skyline plot demographic reconstructions. Conclusions There is now more genetic information available than ever before and large meta-data sets offer great opportunities to explore new and exciting avenues of research. However, compiling multi-study datasets still remains a technically challenging prospect. The mtDNAcombine package provides a pipeline to streamline the process of downloading, curating, and analysing sequence data, guiding the process of compiling data sets from the online database GenBank.

Phylogenomics and phylodynamics of SARS-CoV-2 retrieved genomes from India

The ongoing SARS-CoV-2 pandemic is one of the biggest outbreaks after the Spanish flu of 1918. Understanding the epidemiology of viral outbreaks is the first step towards vaccine development programs. This is the first phylodynamics study attempted on of SARS-CoV-2 genomes from India to infer its current evolution in the context of an ongoing pandemic. Out of 286 retrieved SARS-CoV-2 whole genomes from India, 138 haplotypes were generated and analyzed. Median-joining network was built to investigate the relatedness of SARS-CoV-2 haplotypes in India. The BDSIR package of BEAST2 was used to calculate the reproduction number (R0) and the infectious rate of the virus. Past and current population trend was investigated using the stamp date method in coalescent Bayesian skyline plot, implemented in BEAST2 and by exponential growth prior in BEAST 1.10.4. Median-joining network reveals two distinct ancestral clusters A and B showing genetic affinities with Wuhan outbreak sample. The network also illustrates the autochthonous development of isolates in a few instances. High basic reproduction number of SARS-nCoV-2 in India points towards the phase of active community transmission. The Bayesian skyline plot revel exponential rise in the effective population size (Ne) of Indian isolates from the first week of January to the first week of April 2020. More genome sequencing and analyses of the virus will be required in coming days to monitor COVID19 after the upliftment of lock down in India.

mtDNAcombine: tools to combine sequences from multiple studies

Today an unprecedented amount of genetic sequence data is stored in publicly available repositories. For decades now, mitochondrial DNA (mtDNA) has been the workhorse of genetic studies, and as a result, there is a large volume of mtDNA data available in these repositories for a wide range of species. Indeed, whilst whole genome sequencing is an exciting prospect for the future, for most non-model organisms’ classical markers such as mtDNA remain widely used. By compiling existing data from multiple original studies, it is possible to build powerful new datasets capable of exploring many questions in ecology, evolution and conservation biology. One key question that these data can help inform is what happened in a species’ demographic past. However, compiling data in this manner is not trivial, there are many complexities associated with data extraction, data quality and data handling. Here we present the mtDNAcombine package, a collection of tools developed to manage some of the major decisions associated with handling multi-study sequence data with a particular focus on preparing mtDNA data for Bayesian Skyline Plot demographic reconstructions.

Independent evolutionary lineage of the clingfish Gobiesox adustus (Gobiesocidae) from Isla del Coco, Costa Rica

Introduction: Isla del Coco is an important protected area for marine fauna in the Eastern Tropical Pacific. In this area, the species that inhabit the intertidal zone have been subject to few studies. One of the species inhabiting these areas is the clingfish Gobiesox adustus (Gobiesocidae). Objective: To analyze for the first time the mitochondrial gene cytochrome oxidase subunit 1 (cox1) of G. adustus’ population from Isla del Coco and compare it with those of continental coast of Costa Rica and Ecuador. Methods: We constructed a haplotype network for these samples. Genetic diversity, distance and structure were calculated by several software. The historical demography of Isla del Coco samples was assessed with the method Bayesian skyline plot as implemented in BEAST2. Results: The samples segregate into three haplogroups: one consisting of the Isla del Coco samples, a second consisting of a subset of the Ecuador samples, and a third consisting of Costa Rica and the remaining Ecuador samples. The genetic distances between the three haplogroups range between 1.6% and 2.1% (uncorrected p-distance), and pairwise ΦST and AMOVA results between the three haplogroups show high and significant values. Conclusions: The Isla del Coco haplogroup showed a Pleistocene population growth, which agrees with demographic patterns found in other marine organisms. The history of isolation of the G. adustus population from Isla del Coco demonstrates the evolutionary independence of this population.

The phylodynamic of H1a genotype measles virus in Jiangsu province, China, 2005-2017

Background: The change on the pressures during viruses evolving will cause changes in phylodynamic. To know phylodynamic characteristic of measles virus in high vaccination coverage era, the phylodynamic characteristic was analyzed using nucleoprotein gene sequences of measles viruses isolated from Jiangsu province of China from 2005 to 2017. Methods: Nucleoprotein gene sequences of measles viruses were used to analyze gene distance and construct phylogenetic tree with Markov chain Monte Carlo algorithm. The mean gene distance within each group was computed with MEGA7.0 software. The phylodynamic of measles virus circulating in Jiangsu province was constructed using Bayesian skyline plot analyses. Results: Our results showed that the decline trend is observed in the gene distance of nucleoprotein gene and effective population size of measles virus with time. Two clusters of H1a genotype shows multiple origins and the extinction of variants with time. Conclusion: These findings highlight that phylodynamic of measles viruses is a helpful tool to assess the effectiveness of epidemic control.

Mitochondrial phylogeography of kinkajous (Procyonidae, Carnivora): maybe not a single ESU

Knowledge of how a species is divided into different genetic units, and the structure among these units, is fundamental to the protection of biodiversity. Procyonidae was one of the families in the Order Carnivora with more success in the colonization of South America. The most divergent species in this family is the kinkajou (Potos flavus). However, knowledge of the genetics and evolution of this species is scarce. We analyzed five mitochondrial genes within 129 individuals of P. flavus from seven Neotropical countries (Mexico, Guatemala, Honduras, Colombia, Ecuador, Peru, and Bolivia). We detected eight different populations or haplogroups, although only three had highly significant bootstrap values (southern Mexico and Central America; northern Peruvian, Ecuadorian, and Colombian Amazon; and north-central Andes and the southern Amazon in Peru). Some analyses showed that the ancestor of the southern Mexico–Central America haplogroup was the first to appear. The youngest haplogroups were those at the most southern area analyzed in Peru and Bolivia. A “borrowed molecular clock” estimated the initial diversification to have occurred around 9.6 million years ago (MYA). All the spatial genetic analyses detected a very strong spatial structure with significant genetic patches (average diameter around 400–500 km) and a clinal isolation by distance among them. The overall sample and all of the haplogroups we detected had elevated levels of genetic diversity, which strongly indicates their long existence. A Bayesian Skyline Plot detected, for the overall sample and for the three most significant haplogroups, a decrease in the number of females within the last 30,000–50,000 years, with a strong decrease in the last 10,000–20,000 years. Our data supported an alignment of some but not all haplogroups with putative morphological subspecies. We have not discounted the possibility of a cryptic kinkajou species.

High genetic connectivity and Population Expansion of Scomber japonicus in the Northern Humboldt Current System revealed by mitochondrial D-Loop region sequences

La caballa, Scomber japonicus soporta una pesquería importante en el Pacífico Sudeste, sin embargo, su genética de poblaciones se desconoce actualmente. En el presente estudio se examinó la estructura genética, el flujo génico y la demografía histórica de esta especie en la parte norte del Sistema de la Corriente de Humboldt. Las muestras fueron colectadas en los veranos del 2013 y 2014 en tres puntos de desembarco de pesca (Paita, Ventanilla e Ilo) cubriendo 12 grados de latitud frente a la costa peruana. Se secuenció un segmento de 532 pb de la región control mitocondrial en 72 individuos, el cual permitió detectar un total de 29 sitios polimórficos, 35 haplotipos, niveles moderados altos de diversidad haplotípica (0.793 – 0.969) y muy bajos niveles de diversidad nucleotídica (0.004 – 0.008). El análisis de flujo génico mostró altos niveles de conectividad entre las poblaciones en las áreas de muestreo. El análisis de varianza molecular (ФST = 0.00868, P = 0.1837), las comparaciones ФST a pares de poblaciones y las pruebas de diferenciación genética confirmaron la carencia de estructuración genética entre las tres localidades. Estos análisis sugieren que los sitios de muestreo analizados pueden ser considerados como un solo grupo genético. El comportamiento migratorio, el alto potencial de dispersión de los estadios tempranos de desarrollo y la ausencia de barreras oceanográficas pueden explicar su homogeneidad genética a lo largo del mar peruano. También se examinó la demografía histórica. Las pruebas de neutralidad, la distribución mismatch y el Bayesian Skyline Plot sugirieron un escenario de expansión poblacional que tuvo lugar durante el Pleistoceno Superior. Este estudio provee información nueva con respecto a la genética de poblaciones de la caballa en el Pacífico Sudeste.