Characterization of adaptation mechanisms in sorghum using a multireference back-cross nested association mapping design and envirotyping.

Identifying the genetic factors impacting the adaptation of crops to environmental conditions is of key interest for conservation and selection purposes. It can be achieved using population genomics, and evolutionary or quantitative genetics. Here we present a sorghum multireference back-cross nested association mapping population composed of 3,901 lines produced by crossing 24 diverse parents to 3 elite parents from West and Central Africa-back-cross nested association mapping. The population was phenotyped in environments characterized by differences in photoperiod, rainfall pattern, temperature levels, and soil fertility. To integrate the multiparental and multi-environmental dimension of our data we proposed a new approach for quantitative trait loci (QTL) detection and parental effect estimation. We extended our model to estimate QTL effect sensitivity to environmental covariates, which facilitated the integration of envirotyping data. Our models allowed spatial projections of the QTL effects in agro-ecologies of interest. We utilized this strategy to analyze the genetic architecture of flowering time and plant height, which represents key adaptation mechanisms in environments like West Africa. Our results allowed a better characterization of well-known genomic regions influencing flowering time concerning their response to photoperiod with Ma6 and Ma1 being photoperiod-sensitive and the region of possible candidate gene Elf3 being photoperiod-insensitive. We also accessed a better understanding of plant height genetic determinism with the combined effects of phenology-dependent (Ma6) and independent (qHT7.1 and Dw3) genomic regions. Therefore, we argue that the West and Central Africa-back-cross nested association mapping and the presented analytical approach constitute unique resources to better understand adaptation in sorghum with direct application to develop climate-smart varieties.

The First Case of Zika Virus Disease in Guinea: Description, Virus Isolation, Sequencing, and Seroprevalence in Local Population.

The Zika virus (ZIKV) is a widespread mosquito-borne pathogen. Phylogenetically, two lineages of ZIKV are distinguished: African and Asian-American. The latter became the cause of the 2015-2016 pandemic, with severe consequences for newborns. In West African countries, the African lineage was found, but there is evidence of the emergence of the Asian-American lineage in Cape Verde and Angola. This highlights the need to not only monitor ZIKV but also sequence the isolates. In this article, we present a case report of Zika fever in a pregnant woman from Guinea identified in 2018. Viral RNA was detected through qRT-PCR in a serum sample. In addition, the seroconversion of anti-Zika IgM and IgG antibodies was detected in repeated blood samples. Subsequently, the virus was isolated from the C6/36 cell line. The detected ZIKV belonged to the African lineage, the Nigerian sublineage. The strains with the closest sequences were isolated from mosquitoes in Senegal in 2011 and 2015. In addition, we conducted the serological screening of 116 blood samples collected from patients presenting to the hospital of Faranah with fevers during the period 2018-2021. As a result, it was found that IgM-positive patients were identified each year and that the seroprevalence varied between 5.6% and 17.1%.

Ngari virus (Orthobunyavirus, Peribunyaviridae) in ixodid ticks collected from cattle in Guinea.

Ngari virus is a mosquito-borne virus belonging to the genus Orthobunyavirus (Peribunyaviridae family). This virus is pathogenic to humans and causes severe illness. Ngari virus is present in several African countries, including Madagascar. Here, we report the detection of Ngari virus in ixodid ticks collected from cows in Guinea. A tick survey was conducted in March-November of 2018 in six regions of Guinea. The sample comprised 710 pools, with a total of 2067 ticks belonging to five species collected from 197 cows. At the initial stage, we screened a subsample of tick pools of vector-borne viruses with a multiplex genus-specific primer panel. In the second stage of the study, we narrowed the search and screened all the samples by qPCR for the detection of Ngari virus. All positive samples were sequenced with primers flanking Ngari virus-specific fragments on the S and M segments. We found Ngari virus in 12 pools that were formed from engorged ticks collected from livestock in three villages of the Kindia and Kankan regions. Sequencing of the S and M segments confirmed that the detected viruses belong to Ngari virus, and the viruses were most similar to the strain Adrar, which was isolated in Mauritania. We detected viral RNA in ticks of the following species: Amblyomma variegatum, Rhipicephalus geigyi, and Rh. (Boophilus) spp. There is no evidence that ixodid ticks are competent vectors of the Ngari virus. Most likely, the ticks obtained the virus through blood from an infected host. The study of engorged ticks can be recommended as a simpler approach for the wide screening of the Ngari virus and subsequent testing of cattle and mosquitos in those locations where the PCR-positive ticks were collected.

Asymptotic normality of the test statistics for the unified relative dispersion and relative variation indexes.

Dispersion indexes with respect to the Poisson and binomial distributions are widely used to assess the conformity of the underlying distribution from an observed sample of the count with one or the other of these theoretical distributions. Recently, the exponential variation index has been proposed as an extension to nonnegative continuous data. This paper aims to gather to study the unified definition of these indexes with respect to the relative variability of a nonnegative natural exponential family of distributions through its variance function. We establish the strong consistency of the plug-in estimators of the indexes as well as their asymptotic normalities. Since the exact distributions of the estimators are not available in closed form, we consider the test of hypothesis relying on these estimators as test statistics with their asymptotic distributions. Simulation studies globally suggest good behaviours of these tests of hypothesis procedures. Applicable examples are analysed, including the lesser-known references such as negative binomial and inverse Gaussian, and improving the very usual case of the Poisson dispersion index. Concluding remarks are made with suggestions of possible extensions.

High risk factors of pancreatic carcinoma.

Over the past decades, cancer has become one of the toughest challenges for health professionals. The epidemiologists are increasingly directing their research efforts on various malignant tumor worldwide. Of note, incidence of cancers is on the rise more quickly in developed countries. Indeed, great endeavors have to be made in the control of the life-threatening disease. As we know it, pancreatic cancer (PC) is a malignant disease with the worst prognosis. While little is known about the etiology of the PC and measures to prevent the condition, so far, a number of risk factors have been identified. Genetic factors, pre-malignant lesions, predisposing diseases and exogenous factors have been found to be linked to PC. Genetic susceptibility was observed in 10% of PC cases, including inherited PC syndromes and familial PC. However, in the remaining 90%, their PC might be caused by genetic factors in combination with environmental factors. Nonetheless, the exact mechanism of the two kinds of factors, endogenous and exogenous, working together to cause PC remains poorly understood. The fact that most pancreatic neoplasms are diagnosed at an incurable stage of the disease highlights the need to identify risk factors and to understand their contribution to carcinogenesis. This article reviews the high risk factors contributing to the development of PC, to provide information for clinicians and epidemiologists.