Genetic regulators of mineral amount in Nelore cattle muscle predicted by a new co-expression and regulatory impact factor approach.

Mineral contents in bovine muscle can affect meat quality, growth, health, and reproductive traits. To better understand the genetic basis of this phenotype in Nelore (Bos indicus) cattle, we analysed genome-wide mRNA and miRNA expression data from 114 muscle samples. The analysis implemented a new application for two complementary algorithms: the partial correlation and information theory (PCIT) and the regulatory impact factor (RIF), in which we included the estimated genomic breeding values (GEBVs) for the phenotypes additionally to the expression levels, originally proposed for these methods. We used PCIT to determine putative regulatory relationships based on significant associations between gene expression and GEBVs for each mineral amount. Then, RIF was adopted to determine the regulatory impact of genes and miRNAs expression over the GEBVs for the mineral amounts. We also investigated over-represented pathways, as well as pieces of evidences from previous studies carried in the same population and in the literature, to determine regulatory genes for the mineral amounts. For example, NOX1 expression level was positively correlated to Zinc and has been described as Zinc-regulated in humans. Based on our approach, we were able to identify genes, miRNAs and pathways not yet described as underlying mineral amount. The results support the hypothesis that extracellular matrix interactions are the core regulator of mineral amount in muscle cells. Putative regulators described here add information to this hypothesis, expanding the knowledge on molecular relationships between gene expression and minerals.Article: 8436

The genetic legacy of the expansion of Bantu-speaking peoples in Africa.

The expansion of people speaking Bantu languages is the most dramatic demographic event in Late Holocene Africa and fundamentally reshaped the linguistic, cultural and biological landscape of the continent1-7. With a comprehensive genomic dataset, including newly generated data of modern-day and ancient DNA from previously unsampled regions in Africa, we contribute insights into this expansion that started 6,000-4,000 years ago in western Africa. We genotyped 1,763 participants, including 1,526 Bantu speakers from 147 populations across 14 African countries, and generated whole-genome sequences from 12 Late Iron Age individuals8. We show that genetic diversity amongst Bantu-speaking populations declines with distance from western Africa, with current-day Zambia and the Democratic Republic of Congo as possible crossroads of interaction. Using spatially explicit methods9 and correlating genetic, linguistic and geographical data, we provide cross-disciplinary support for a serial-founder migration model. We further show that Bantu speakers received significant gene flow from local groups in regions they expanded into. Our genetic dataset provides an exhaustive modern-day African comparative dataset for ancient DNA studies10 and will be important to a wide range of disciplines from science and humanities, as well as to the medical sector studying human genetic variation and health in African and African-descendant populations

The genetic legacy of the expansion of Bantu-speaking peoples in Africa

DATA AVAILABILITY : SNP array genotype data of modern-day African populations and whole-genome data of aDNA individuals generated in this project were made available through the European Genome-Phenome Archive (EGA) data repository (EGA accessory nos. EGAS50000000006 and EGAS00001007519 for modern and aDNA, respectively). Controlled-access policies guided by participant consent agreements will be implemented by the AfricanNeo Data Access Committee (AfricanNeo DAC accessory no. EGAC00001003398). Authorized NIH DAC granted data access to C.M.S. for the controlled-access genetic data deposited in the NIH dbGAP repository (accession code phs001396.v1.p1 and project ID 19895). C.M.S. was granted data access to whole-genome sequencing data deposed by the H3Africa Consortium (EGA dataset accessory nos. EGAD00001004220, EGAD00001004316, EGAD00001004334, EGAD00001004393, EGAD00001004448, EGAD00001004505, EGAD00001004533, EGAD00001004557 and EGAD00001005076). Interactive map-based visualizations were created using the Python library bokeh v.3.0.0 and maps were provided by CartoDB (CARTO 2023), other base maps were provided by GoogleMaps (Google 2023) or created using Python libraries (plotly v.5.17.0 and shapely v.1.8.4); R packages (rworldmap v.1.3.6, plotmaps v.1.0, rEEMSplots and rEEMSplots2); and one inhouse vector map in MapInfo interchange format based on the WGS-84 projection.CODE AVAILABILITY : Code and interactive plots used for plotting are available in two online repositories (GitHub https://github.com/Schlebusch-lab/Expansion_of_BSP_peer-reviewed_article and figshare https://doi.org/10.6084/m9.figshare.24107718).SUPPLEMENTARY INFORMATION. Supplementary Methods, Notes 1–12, Figures 1–107, and references.SUPPLEMENTARY TABLES. Supplementary Tables 1–15.The expansion of people speaking Bantu languages is the most dramatic demographic event in Late Holocene Africa and fundamentally reshaped the linguistic, cultural and biological landscape of the continent. With a comprehensive genomic dataset, including newly generated data of modern-day and ancient DNA from previously unsampled regions in Africa, we contribute insights into this expansion that started 6,000–4,000 years ago in western Africa. We genotyped 1,763 participants, including 1,526 Bantu speakers from 147 populations across 14 African countries, and generated whole-genome sequences from 12 Late Iron Age individuals. We show that genetic diversity amongst Bantu-speaking populations declines with distance from western Africa, with current-day Zambia and the Democratic Republic of Congo as possible crossroads of interaction. Using spatially explicit methods and correlating genetic, linguistic and geographical data, we provide cross-disciplinary support for a serial-founder migration model. We further show that Bantu speakers received significant gene flow from local groups in regions they expanded into. Our genetic dataset provides an exhaustive modern-day African comparative dataset for ancient DNA studies and will be important to a wide range of disciplines from science and humanities, as well as to the medical sector studying human genetic variation and health in African and African-descendant populations.Open access funding provided by Uppsala University.http://www.nature.com/naturehj2024BiochemistryGeneticsMicrobiology and Plant PathologyNon

Closing the Gaps in Genomic Research

Despite Africa's central role in the origin of our species, our knowledge of the genomic diversity in Africa is remarkably sparse. A recent publication by Choudhury et al. underscores the scientific imperative for a broader characterisation of African genomic diversity to better understand demographic history and improve global human health

Impact of climate change and man-made irrigation systems on the transmission risk, long-term trend and seasonality of human and animal fascioliasis in Pakistan

Large areas of the province of Punjab, Pakistan are endemic for fascioliasis, resulting in high economic losses due to livestock infection but also affecting humans directly. The prevalence in livestock varies pronouncedly in space and time (1-70%). Climatic factors influencing fascioliasis presence and potential spread were analysed based on data from five meteorological stations during 1990-2010. Variables such as wet days (Mt), water-budget-based system (Wb-bs) indices and the normalized difference vegetation index (NDVI), were obtained and correlated with geographical distribution, seasonality patterns and the two-decade evolution of fascioliasis in livestock throughout the province. The combined approach by these three indices proved to furnish a useful tool to analyse the complex epidemiology that includes (i) sheep-goats and cattlebuffaloes presenting different immunological responses to fasciolids; (ii) overlap of Fasciola hepatica and F. gigantica; (iii) co-existence of highlands and lowlands in the area studied; and (iv) disease transmission following bi-seasonality with one peak related to natural rainfall and another peak related to man-made irrigation. Results suggest a human infection situation of concern and illustrate how climate and anthropogenic environment modifications influence both geographical distribution and seasonality of fascioliasis risks. Increased fascioliasis risk throughout the Punjab plain and its decrease in the northern highlands of the province became evident during the study period. The high risk in the lowlands is worrying given that Punjab province largely consists of low-altitude, highly irrigated plains. The importance of livestock in this province makes it essential to prioritise adequate control measures. An annual treatment scheme to control the disease is recommended to be applied throughout the whole province

Complex genetic admixture histories reconstructed with Approximate Bayesian Computation

Admixture is a fundamental evolutionary process that has influenced genetic patterns in numerous species. Maximum-likelihood approaches based on allele frequencies and linkage-disequilibrium have been extensively used to infer admixture processes from genome-wide data sets, mostly in human populations. Nevertheless, complex admixture histories, beyond one or two pulses of admixture, remain methodologically challenging to reconstruct. We developed an Approximate Bayesian Computation (ABC) framework to reconstruct highly complex admixture histories from independent genetic markers. We built the software package MetHis to simulate independent SNPs or microsatellites in a two-way admixed population for scenarios with multiple admixture pulses, monotonically decreasing or increasing recurring admixture, or combinations of these scenarios. MetHis allows users to draw model-parameter values from prior distributions set by the user, and, for each simulation, MetHis can calculate numerous summary statistics describing genetic diversity patterns and moments of the distribution of individual admixture fractions. We coupled MetHis with existing machine-learning ABC algorithms and investigated the admixture history of admixed populations. Results showed that random forest ABC scenario-choice could accurately distinguish among most complex admixture scenarios, and errors were mainly found in regions of the parameter space where scenarios were highly nested, and, thus, biologically similar. We focused on African American and Barbadian populations as two study-cases. We found that neural network ABC posterior parameter estimation was accurate and reasonably conservative under complex admixture scenarios. For both admixed populations, we found that monotonically decreasing contributions over time, from Europe and Africa, explained the observed data more accurately than multiple admixture pulses. This approach will allow for reconstructing detailed admixture histories when maximum-likelihood methods are intractable

Identification of ancestry proportions in admixed groups across the Americas using clinical pharmacogenomic SNP panels

We evaluated the performance of three PGx panels to estimate biogeographical ancestry: the DMET panel, and the VIP and Preemptive PGx panels described in the literature. Our analysis indicate that the three panels capture quite well the individual variation in admixture proportions observed in recently admixed populations throughout the Americas, with the Preemptive PGx and DMET panels performing better than the VIP panel. We show that these panels provide reliable information about biogeographic ancestry and can be used to guide the implementation of PGx clinical decision-support (CDS) tools. We also report that using these panels it is possible to control for the effects of population stratification in association studies in recently admixed populations, as exemplified with a warfarin dosing GWA study in a sample from Brazil

Demographic and Selection Histories of Populations Across the Sahel/Savannah Belt

The Sahel/Savannah belt harbors diverse populations with different demographic histories and different subsistence patterns. However, populations from this large African region are notably under-represented in genomic research. To investigate the population structure and adaptation history of populations from the Sahel/Savannah space, we generated dense genome-wide genotype data of 327 individuals-comprising 14 ethnolinguistic groups, including 10 previously unsampled populations. Our results highlight fine-scale population structure and complex patterns of admixture, particularly in Fulani groups and Arabic-speaking populations. Among all studied Sahelian populations, only the Rashaayda Arabic-speaking population from eastern Sudan shows a lack of gene flow from African groups, which is consistent with the short history of this population in the African continent. They are recent migrants from Saudi Arabia with evidence of strong genetic isolation during the last few generations and a strong demographic bottleneck. This population also presents a strong selection signal in a genomic region around the CNR1 gene associated with substance dependence and chronic stress. In Western Sahelian populations, signatures of selection were detected in several other genetic regions, including pathways associated with lactase persistence, immune response, and malaria resistance. Taken together, these findings refine our current knowledge of genetic diversity, population structure, migration, admixture and adaptation of human populations in the Sahel/Savannah belt and contribute to our understanding of human history and health

A genetic and linguistic analysis of the admixture histories of the islands of Cabo Verde

From the 15th to the 19th century, the Trans-Atlantic Slave-Trade (TAST) influenced the genetic and cultural diversity of numerous populations. We explore genomic and linguistic data from the nine islands of Cabo Verde, the earliest European colony of the era in Africa, a major Slave-Trade platform between the 16th and 19th centuries, and a previously uninhabited location ideal for investigating early admixture events between Europeans and Africans. Using local-ancestry inference approaches, we find that genetic admixture in Cabo Verde occurred primarily between Iberian and certain Senegambian populations, although forced and voluntary migrations to the archipelago involved numerous other populations. Inter-individual genetic and linguistic variation recapitulates the geographic distribution of individuals’ birth-places across Cabo Verdean islands, following an isolation-by-distance model with reduced genetic and linguistic effective dispersals within the archipelago, and suggesting that Kriolu language variants have developed together with genetic divergences at very reduced geographical scales. Furthermore, based on approximate bayesian computation inferences of highly complex admixture histories, we find that admixture occurred early on each island, long before the 18th-century massive TAST deportations triggered by the expansion of the plantation economy in Africa and the Americas, and after this era mostly during the abolition of the TAST and of slavery in European colonial empires. Our results illustrate how shifting socio-cultural relationships between enslaved and non-enslaved communities during and after the TAST, shaped enslaved-African descendants’ genomic diversity and structure on both sides of the Atlantic

The ancestry and geographical origins of St Helena's liberated Africans

The island of St Helena played a crucial role in the suppression of the transatlantic slave trade. Strategically located in the middle of the South Atlantic, it served as a staging post for the Royal Navy and reception point for enslaved Africans who had been "liberated"from slave ships intercepted by the British. In total, St Helena received approximately 27,000 liberated Africans between 1840 and 1867. Written sources suggest that the majority of these individuals came from West Central Africa, but their precise origins are unknown. Here, we report the results of ancient DNA analyses that we conducted as part of a wider effort to commemorate St Helena's liberated Africans and to restore knowledge of their lives and experiences. We generated partial genomes (0.1-0.53) for 20 individuals whose remains had been recovered during archaeological excavations on the island. We compared their genomes with genotype data for over 3,000 present-day individuals from 90 populations across sub-Saharan Africa and conclude that the individuals most likely originated from different source populations within the general area between northern Angola and Gabon. We also find that the majority (17/20) of the individuals were male, supporting a well-documented sex bias in the latter phase of the transatlantic slave trade. The study expands our understanding of St Helena's liberated African community and illustrates how ancient DNA analyses can be used to investigate the origins and identities of individuals whose lives were bound up in the story of slavery and its abolition