Imputation of ancient canid genomes reveals inbreeding history over the past 10,000 years
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ABSTRACT:
PROVIDER: PRJEB73844 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:DCEG Imputation Reference Dataset
| PRJNA75845 | ENA
Project description:The genomic causes of inbreeding depression are poorly known. Several studies have found widespread transcriptomic alterations in inbred organisms, but it remains unclear which of these alterations are causes of the depression and which are mere responses to the ensuing physiological stress. We made a c-DNA microarray analysis in Drosophila melanogaster attempting to differentiate causes from responses of inbreeding depression. The rationale of the experiment was that, while depression is a general phenomenon producing similar consequences in different inbred lines, its first genetic causes would be different for each inbred line, as they are expected to be caused by the fixation of rare deleterious genes. Many changes in expression were common to all sets, but fourteen genes, grouped in four expression clusters, showed strong set-specific changes, and were therefore candidates to be sources of the inbreeding depression observed.
2013-05-31 | GSE47176 | GEO
Project description:Missing values in proteomic data sets have real consequences on downstream data analysis and reproducibility. Although several imputation methods exist to handle missing values, no single imputation method is best suited for a diverse range of data sets, and no clear strategy exists for evaluating imputation methods for large-scale DIA-MS data sets, especially at different levels of protein quantification. To navigate through the different imputation strategies available in the literature, we have established a workflow to assess imputation methods on large-scale label-free DIA-MS data sets. We used three DIA-MS data sets with real missing values to evaluate eight different imputation methods with multiple parameters at different levels of protein quantification; dilution series data set, a small pilot data set, and a larger proteomic data set.
2021-05-07 | PXD023012 | Pride
Project description:Missing values in proteomic data sets have real consequences on downstream data analysis and reproducibility. Although several imputation methods exist to handle missing values, no single imputation method is best suited for a diverse range of data sets, and no clear strategy exists for evaluating imputation methods for large-scale DIA-MS data sets, especially at different levels of protein quantification. To navigate through the different imputation strategies available in the literature, we have established a workflow to assess imputation methods on large-scale label-free DIA-MS data sets. We used three DIA-MS data sets with real missing values to evaluate eight different imputation methods with multiple parameters at different levels of protein quantification; dilution series data set, a small pilot data set, and a larger proteomic data set.
2021-05-07 | PXD022996 | Pride
Project description:Missing values in proteomic data sets have real consequences on downstream data analysis and reproducibility. Although several imputation methods exist to handle missing values, no single imputation method is best suited for a diverse range of data sets, and no clear strategy exists for evaluating imputation methods for large-scale DIA-MS data sets, especially at different levels of protein quantification. To navigate through the different imputation strategies available in the literature, we have established a workflow to assess imputation methods on large-scale label-free DIA-MS data sets. We used three DIA-MS data sets with real missing values to evaluate eight different imputation methods with multiple parameters at different levels of protein quantification; dilution series data set, a small pilot data set, and a larger proteomic data set of clinical ovarian cancer patient samples.
2021-05-07 | PXD023040 | Pride
Project description:The genomic causes of inbreeding depression are poorly known. Several studies have found widespread transcriptomic alterations in inbred organisms, but it remains unclear which of these alterations are causes of the depression and which are mere responses to the ensuing physiological stress. We made a c-DNA microarray analysis in Drosophila melanogaster attempting to differentiate causes from responses of inbreeding depression. The rationale of the experiment was that, while depression is a general phenomenon producing similar consequences in different inbred lines, its first genetic causes would be different for each inbred line, as they are expected to be caused by the fixation of rare deleterious genes. Many changes in expression were common to all sets, but fourteen genes, grouped in four expression clusters, showed strong set-specific changes, and were therefore candidates to be sources of the inbreeding depression observed. We took four sets of inbred sublines, each set descending from a different founding pair obtained from a large outbred stock, and compared the expression of the three most depressed sublines and the three least depressed sublines from each set.
2013-05-31 | E-GEOD-47176 | biostudies-arrayexpress
Project description:Data analysis is a critical part of quantitative proteomics studies in interpreting biological questions. Numerous computational tools including protein quantification, imputation, and differential expression (DE) analysis were generated in the past decade. However, searching optimized tools is still an unsolved issue. Moreover, due to the rapid development of RNA-Seq technology, a vast number of DE analysis methods are created. Applying these newly developed RNA-Seq-oriented tools to proteomics data is still a question that needs to be addressed. In order to benchmark these analysis methods, a proteomics dataset constituted the proteins derived from human, yeast, and drosophila with different ratios were generated. Based on this dataset, DE analysis tools (including array-based and RNA-Seq based), imputation algorithms, and protein quantification methods were compared and benchmarked. This study provided useful information on analyzing quantitative proteomics datasets. All the methods used in this study were integrated into Perseus which are available at https://www.maxquant.org/perseus.
2022-11-16 | PXD029891 | JPOST Repository
Project description:Using genome-wide data of 89 ancient individuals dated to 5100 to 100 years before the present (B.P.) from 29 sites across the Tibetan Plateau, we found plateau-specific ancestry across plateau populations, with substantial genetic structure indicating high differentiation before 2500 B.P. Northeastern plateau populations rapidly showed admixture associated with millet farmers by 4700 B.P. in the Gonghe Basin. High genetic similarity on the southern and southwestern plateau showed population expansion along the Yarlung Tsangpo River since 3400 years ago. Central and southeastern plateau populations revealed extensive genetic admixture within the plateau historically, with substantial ancestry related to that found in southern and southwestern plateau populations. Over the past ~700 years, substantial gene flow from lowland East Asia further shaped the genetic landscape of present-day plateau populations. The high-altitude adaptive EPAS1 allele was found in plateau populations as early as in a 5100-year-old individual and showed a sharp increase over the past 2800 years.
| S-EPMC10022901 | biostudies-literature
Project description:We assembled genome-wide data from 271 ancient Iberians, of whom 176 are from the largely unsampled period after 2000 BCE, thereby providing a high-resolution time transect of the Iberian Peninsula. We document high genetic substructure between northwestern and southeastern hunter-gatherers before the spread of farming. We reveal sporadic contacts between Iberia and North Africa by ~2500 BCE and, by ~2000 BCE, the replacement of 40% of Iberia's ancestry and nearly 100% of its Y-chromosomes by people with Steppe ancestry. We show that, in the Iron Age, Steppe ancestry had spread not only into Indo-European-speaking regions but also into non-Indo-European-speaking ones, and we reveal that present-day Basques are best described as a typical Iron Age population without the admixture events that later affected the rest of Iberia. Additionally, we document how, beginning at least in the Roman period, the ancestry of the peninsula was transformed by gene flow from North Africa and the eastern Mediterranean.
| S-EPMC6436108 | biostudies-literature
Project description:While archaeological sciences have made great advances over the last decades through combining archaeological evidence and natural sciences in order to push borders for the understanding of archaeological contexts, traditional archaeology still holds an immense latent potential. Such potential can be realized through baseline projects that pull together unexplored bodies of material culture and study these in detail in order to investigate their significance for the understanding of the human past. This paper presents such a large-scale baseline study and focuses on the presentation of the results emerging from the recently compiled corpus of more than 3700 funerary portraits stemming from one location in the ancient world, Roman Palmyra, an oasis city in the Syrian Desert. The analysis of the chronological development of the numerous portraits allows us to follow the fluctuations in the production of these portraits over approximately 300 years. Here we discuss and review the developments in connection with historical sources and discuss until now unknown events, which have emerged through the data analysis. The paper brings to the forefront the significance of social science baseline projects, which often do not receive enough attention or funding, but which in fact are fundamental for furthering our understanding of the human past and push borders for the directions in which we can take such studies in the future.
| S-EPMC8565770 | biostudies-literature