Genomic Footprints Of Selection Research Articles

Genomic footprints of selection in early-and late-flowering pearl millet landraces.

Pearl millet is among the top three-cereal production in one of the most climate vulnerable regions, sub-Saharan Africa. Its Sahelian origin makes it adapted to grow in poor sandy soils under low soil water regimes. Pearl millet is thus considered today as one of the most interesting crops to face the global warming. Flowering time, a trait highly correlated with latitude, is one of the key traits that could be modulated to face future global changes. West African pearl millet landraces, can be grouped into early- (EF) and late-flowering (LF) varieties, each flowering group playing a specific role in the functioning and resilience of Sahelian smallholders. The aim of this study was thus to detect genes linked to flowering but also linked to relevant traits within each flowering group. We thus investigated genomic and phenotypic diversity in 109 pearl millet landrace accessions, i.e., 66 early-flowering and 43 late-flowering, grown in the groundnut basin, the first area of rainfed agriculture in Senegal dominated by dry cereals (millet, maize, and sorghum) and legumes (groundnuts, cowpeas). We were able to confirm the role of PhyC gene in pearl millet flowering and identify several other genes that appear to be as much as important, such as FSR12 and HAC1. HAC1 and two other genes appear to be part of QTLs previously identified and deserve further investigation. At the same time, we were able to highlight a several genes and variants that could contribute to the improvement of pearl millet yield, especially since their impact was demonstrated across flowering cycles.

Simultaneous testing of rule- and model-based approaches for runs of homozygosity detection opens up a window into genomic footprints of selection in pigs

BackgroundPast selection events left footprints in the genome of domestic animals, which can be traced back by stretches of homozygous genotypes, designated as runs of homozygosity (ROHs). The analysis of common ROH regions within groups or populations displaying potential signatures of selection requires high-quality SNP data as well as carefully adjusted ROH-defining parameters. In this study, we used a simultaneous testing of rule- and model-based approaches to perform strategic ROH calling in genomic data from different pig populations to detect genomic regions under selection for specific phenotypes.ResultsOur ROH analysis using a rule-based approach offered by PLINK, as well as a model-based approach run by RZooRoH demonstrated a high efficiency of both methods. It underlined the importance of providing a high-quality SNP set as input as well as adjusting parameters based on dataset and population for ROH calling. Particularly, ROHs ≤ 20 kb were called in a high frequency by both tools, but to some extent covered different gene sets in subsequent analysis of ROH regions common for investigated pig groups. Phenotype associated ROH analysis resulted in regions under potential selection characterizing heritage pig breeds, known to harbour a long-established breeding history. In particular, the selection focus on fitness-related traits was underlined by various ROHs harbouring disease resistance or tolerance-associated genes. Moreover, we identified potential selection signatures associated with ear morphology, which confirmed known candidate genes as well as uncovered a missense mutation in the ABCA6 gene potentially supporting ear cartilage formation.ConclusionsThe results of this study highlight the strengths and unique features of rule- and model-based approaches as well as demonstrate their potential for ROH analysis in animal populations. We provide a workflow for ROH detection, evaluating the major steps from filtering for high-quality SNP sets to intersecting ROH regions. Formula-based estimations defining ROHs for rule-based method show its limits, particularly for efficient detection of smaller ROHs. Moreover, we emphasize the role of ROH detection for the identification of potential footprints of selection in pigs, displaying their breed-specific characteristics or favourable phenotypes.

A tiered approach to genome-wide association analysis for the adherence of hulls to the caryopsis of barley seeds reveals footprints of selection

BackgroundSeeds of domesticated barley are grouped into two distinct types, which differ in morphology. Caryopses covered by adaxial (palea) and abaxial (lemma) hulls that tightly adhere to the pericarp at maturity give rise to hulled seeds whereas caryopses without adhering hulls give rise to naked seeds. The naked caryopsis character is an essential trait regarding the end use of barley.ResultsTo uncover the genetic basis of the trait, a genome-wide association study (GWAS) has been performed in a panel comprising 222 2-rowed and 303 6-rowed spring barley landrace accessions. In addition to the well-described Nud locus on chromosome 7H, three novel loci showed strong associations with the trait: the first locus on 2H was specifically detected in 6-rowed accessions, the second locus on 3H was found in 2-rowed accessions from Eurasia and the third locus on 6H was revealed in 6-rowed accessions from Ethiopia. PCR analysis of naked accessions also confirmed the absence of a 17 kb region harboring the Nud gene on chromosome 7H for all but one naked accession. The latter was characterized by a slightly variant phenotype of the caryopsis.ConclusionOur findings provide evidence of the pervasiveness of the 17 kb deletion in spring barley from different geographic regions and at the same time reveal genomic footprints of selection in naked barley, which follow both geographic and morphological patterns.

Linking genetic mechanisms of heterozygosity-fitness correlations to footprints of selection at single loci

Investigations of heterozygosity-fitness correlations (HFCs) are central to the understanding how genetic diversity is maintained in natural populations. Advanced genome-wide approaches will enrich the number of functional loci to be tested. We argue that a combined analysis of the genetic mechanisms of HFCs and selection signals at single loci will allow researchers to better understand the micro-evolutionary basis of HFCs. Different dominance relationships among the alleles at the locus can lead to positive, negative or null HFCs depending on the allele frequency distribution. These scenarios differ in the temporal stability of the HFCs and in the patterns of allele frequency changes over time. Here, we describe a simple theoretical framework that links the analyses of heterozygosity-fitness associations (ecological timescale) with tests for selection signals (evolutionary timescale). Different genomic footprints of selection can be expected for the different underlying genetic mechanisms of HFCs, and this information can be independently used for the classification of HFCs. We suggest that in addition to inbreeding and single-locus overdominant effects also loci under directional selection could play a significant role in the development of heterozygosity-fitness effects in large natural populations under recent or fluctuating ecological changes.