Why most Principal Component Analyses (PCA) in population genetic studies are wrong

Principal Component Analysis (PCA) is a multivariate analysis that allows reduction of the complexity of datasets while preserving data's covariance and visualizing the information on colorful scatterplots, ideally with only a minimal loss of information. PCA applications are extensively used as the foremost analyses in population genetics and related fields (e.g., animal and plant or medical genetics), implemented in well-cited packages like EIGENSOFT and PLINK. PCA outcomes are used to shape study design, identify and characterize individuals and populations, and draw historical and ethnobiological conclusions on origins, evolution, whereabouts, and relatedness. The replicability crisis in science has prompted us to evaluate whether PCA results are reliable, robust, and replicable. We employed an intuitive color-based model alongside human population data for eleven common test cases. We demonstrate that PCA results are artifacts of the data and that they can be easily manipulated to generate desired outcomes. PCA results may not be reliable, robust, or replicable as the field assumes. Our findings raise concerns on the validity of results reported in the literature of population genetics and related fields that place a disproportionate reliance upon PCA outcomes and the insights derived from them. We conclude that PCA may have a biasing role in genetic investigations. An alternative mixed-admixture population genetic model is discussed.

Understanding genetic diversity, structure and population differentiation in selected wild species and cultivated Indian and exotic rose varieties based on microsatellite allele frequencies

Roses are the most important commercial ornamental plants grown for flowers, perfumery and nutraceutical compounds. Commercially cultivated roses (Rosa × hybrida L.) are complex interspecific hybrids probably derived from 8-10 wild species among the large diversity of 130-200 species in genus Rosa. Wild germplasm is a primary source of variability and plays a major role in improving existing varieties by broadening their genetic base. In the present investigation, we have utilized the previously identified SSR primers for studying the diversity among 148 selected rose genotypes, including wild species and cultivated varieties of Indian and exotic origin. A total of 88 alleles was scored using 30 polymorphic loci; they produced average 2.9±1 alleles per locus. Polymorphism information content (PIC) values for different SSR loci ranged from 0.08 to 0.8 with a mean value of 0.5±0.2. The neighbor-joining tree generated based on Nei’s (1978) genetic distance values grouped the population into three major clusters. Cluster-I and II consists of all modern rose cultivars (Rosa × hybrida L.) originated from India and cluster-III consists of all exotic cultivars, wild species and a few cultivars from India. STRUCTURE analysis based on microsatellite allelic data, partitioned the total rose genotypes into four different sub-populations with some individual genotypes having genomic admixture. Population subdivision estimates, FST between different subpopulations ranged from 0.01-0.15 indicates low to moderate level of divergence existing among the rose cultivars and germplasm. Population differentiation in rose cultivars and wild species corresponds to their geographical origin and lineages. Analysis of molecular variance (AMOVA) results revealed that 83.12 % of the variance was accounted for by within sub-groups followed by significant levels of variation among the populations (10.42%) and least variance (6.46%) was noticed among individuals within groups.

Hybrid speciation leads to novel male secondary sexual ornamentation of an Amazonian bird

Hybrid speciation is rare in vertebrates, and reproductive isolation arising from hybridization is infrequently demonstrated. Here, we present evidence supporting a hybrid-speciation event involving the genetic admixture of the snow-capped (Lepidothrix nattereri) and opal-crowned (Lepidothrix iris) manakins of the Amazon basin, leading to the formation of the hybrid species, the golden-crowned manakin (Lepidothrix vilasboasi). We used a genome-wide SNP dataset together with analysis of admixture, population structure, and coalescent modeling to demonstrate that the golden-crowned manakin is genetically an admixture of these species and does not represent a hybrid zone but instead formed through ancient genetic admixture. We used spectrophotometry to quantify the coloration of the species-specific male crown patches. Crown patches are highly reflective white (snow-capped manakin) or iridescent whitish-blue to pink (opal-crowned manakin) in parental species but are a much less reflective yellow in the hybrid species. The brilliant coloration of the parental species results from nanostructural organization of the keratin matrix feather barbs of the crown. However, using electron microscopy, we demonstrate that the structural organization of this matrix is different in the two parental species and that the hybrid species is intermediate. The intermediate nature of the crown barbs, resulting from past admixture appears to have rendered a duller structural coloration. To compensate for reduced brightness, selection apparently resulted in extensive thickening of the carotenoid-laden barb cortex, producing the yellow crown coloration. The evolution of this unique crown-color signal likely culminated in premating isolation of the hybrid species from both parental species.

Evidence of population specific selection inferred from 289 genome sequences of Nilo-Saharan and Niger-Congo linguistic groups in Africa

BackgroundThere are over 2000 genetically diverse ethno-linguistic groups in Africa that could help decipher human evolutionary history and the genetic basis of phenotypic variation. We have sequenced 300 genomes from Niger-Congo populations from six sub-Saharan African countries (Uganda, Democratic Republic of Congo, Cameroon, Zambia, Ivory Coast, Guinea) and a Nilo-Saharan population from Uganda. Of these, we analysed 289 samples for population structure, genetic admixture, population history and signatures of selection. These samples were collected as part of the TrypanoGEN consortium project [1].ResultsThe population genetic structure of the 289 individuals revealed four clusters, which correlated with ethno-linguistic group and geographical latitude. These were the West African Niger-Congo A, Central African Niger-Congo B, East African Niger-Congo B and the Nilo-Saharan. We observed a spatial distribution of positive natural selection signatures in genes previously associated with AIDS, Tuberculosis, Malaria and Human African Trypanosomiasis among the TrypanoGEN samples. Having observed a marked difference between the Nilo-Saharan Lugbara and Niger-Congo populations, we identified four genes (APOBEC3G, TOP2B, CAPN9, LANCL2), which are highly differentiated between the two ethnic groups and under positive selection in the Lugbara population (_iHS -log p > 3.0, Rsb -log p > 3.0, Fst > 0.1 bonferroni p > 1.8x10e4).ConclusionThe signatures that differentiate ethnically distinct populations could provide information on the specific ecological adaptations with respect to disease history and susceptibility/resistance. For instance in this study we identified APOBEC3G which is believed to be involved in the susceptibility of the Nilo-Saharan Lugbara population to Hepatitis B virus infection.