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Genetic and genomic architectures of traits under selection are key factors influencing evolutionary responses. Yet, knowledge of their impacts has been limited by a widespread assumption that most traits are controlled by unlinked polygenic architectures. Recent advances in genome sequencing and eco-evolutionary modeling are unlocking the potential for integrating genomic information into predictions of population responses to environmental change. Using eco-evolutionary simulations, we demonstrate that hypothetical single-locus control of a life history trait produces highly variable and unpredictable harvesting-induced evolution relative to the classically applied multilocus model. Single-locus control of complex traits is thought to be uncommon, yet blocks of linked genes, such as those associated with some types of structural genomic variation, have emerged as taxonomically widespread phenomena. Inheritance of linked architectures resembles that of single loci, thus enabling single-locus-like modeling of polygenic adaptation. Yet, the number of loci, their effect sizes, and the degree of linkage among them all occur along a continuum. We review how linked architectures are often associated, directly or indirectly, with traits expected to be under selection from anthropogenic stressors and are likely to play a large role in adaptation to environmental disturbance. We suggest using single-locus models to explore evolutionary extremes and uncertainties when the trait architecture is unknown, refining parameters as genomic information becomes available, and explicitly incorporating linkage among loci when possible. By overestimating the complexity (e.g., number of independent loci) of the genomic architecture of traits under selection, we risk underestimating the complexity (e.g., nonlinearity) of their evolutionary dynamics.
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http://dx.doi.org/10.1093/jhered/esaa020 | DOI Listing |
Plant Mol Biol
December 2024
Institute of Botany, Jiangsu Province and Chinese Academy of Sciences, Nanjing, 210014, China.
Dioscorea alata, a key tuber crop for global food security, is threatened by anthracnose disease caused by Colletotrichum gloeosporioides. However, identification of functional resistance genes against C. gloeosporioides in D.
View Article and Find Full Text PDFFront Genet
December 2024
Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, Republic of Korea.
Multi-omics data integration has become increasingly crucial for a deeper understanding of the complexity of biological systems. However, effectively integrating and analyzing multi-omics data remains challenging due to their heterogeneity and high dimensionality. Existing methods often struggle with noise, redundant features, and the complex interactions between different omics layers, leading to suboptimal performance.
View Article and Find Full Text PDFJ Transl Med
December 2024
Department of Ophthalmology, Zhujiang Hospital, Southern Medical University, 253 Industrial Avenue, Guangzhou, 510282, China.
Background: Diabetic retinopathy (DR) is the most important complication of Type 2 Diabetes (T2D) in eyes. Despite its prevalence, the early detection and management of DR continue to pose considerable challenges. Our research aims to elucidate potent drug targets that could facilitate the identification of DR and propel advancements in its therapeutic strategies.
View Article and Find Full Text PDFBMC Bioinformatics
December 2024
Albert Szent-Györgyi Health Centre, University of Szeged, Korányi fasor 14-15, Szeged, H-6725, Csongrád-Csanád, Hungary.
Background: Accurate prediction of copy number variations (CNVs) from targeted capture next-generation sequencing (NGS) data relies on effective normalization of read coverage profiles. The normalization process is particularly challenging due to hidden systemic biases such as GC bias, which can significantly affect the sensitivity and specificity of CNV detection. In many cases, the kit manifests provide only the genome coordinates of the targeted regions, and the exact bait design of the oligo capture baits is not available.
View Article and Find Full Text PDFCommun Biol
December 2024
Department of Gastroenterology, The First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China.
Comorbidity among atopic diseases (ADs) and gastrointestinal diseases (GIDs) has been repeatedly demonstrated by epidemiological studies, whereas the shared genetic liability remains largely unknown. Here we establish an atlas of the shared genetic architecture between 10 ADs or related traits and 11 GIDs, comprehensively investigating the comorbidity-associated genomic regions, cell types, genes and genetically predicted causality. Although distinct genetic correlations between AD-GID are observed, including 14 genome-wide and 28 regional correlations, genetic factors of Crohn's disease (CD), ulcerative colitis (UC), celiac disease and asthma subtypes are converged on CD4 T cells consistently across relevant tissues.
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