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      Evolution of Human-Specific Alleles Protecting Cognitive Function of Grandmothers

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          Abstract

          The myelomonocytic receptor CD33 (Siglec-3) inhibits innate immune reactivity by extracellular V-set domain recognition of sialic acid (Sia)-containing “self-associated molecular patterns” (SAMPs). We earlier showed that V-set domain-deficient CD33-variant allele, protective against late-onset Alzheimer’s Disease (LOAD), is derived and specific to the hominin lineage. We now report multiple hominin-specific CD33 V-set domain mutations. Due to hominin-specific, fixed loss-of-function mutation in the CMAH gene, humans lack N-glycolylneuraminic acid (Neu5Gc), the preferred Sia-ligand of ancestral CD33. Mutational analysis and molecular dynamics (MD)-simulations indicate that fixed change in amino acid 21 of hominin V-set domain and conformational changes related to His45 corrected for Neu5Gc-loss by switching to N-acetylneuraminic acid (Neu5Ac)-recognition. We show that human-specific pathogens Neisseria gonorrhoeae and Group B Streptococcus selectively bind human CD33 (huCD33) as part of immune-evasive molecular mimicry of host SAMPs and that this binding is significantly impacted by amino acid 21 modification. In addition to LOAD-protective CD33 alleles, humans harbor derived, population-universal, cognition-protective variants at several other loci. Interestingly, 11 of 13 SNPs in these human genes (including CD33) are not shared by genomes of archaic hominins: Neanderthals and Denisovans. We present a plausible evolutionary scenario to compile, correlate, and comprehend existing knowledge about huCD33-evolution and suggest that grandmothering emerged in humans.

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          MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets.

          We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been optimized for use on 64-bit computing systems for analyzing larger datasets. Researchers can now explore and analyze tens of thousands of sequences in Mega The new version also provides an advanced wizard for building timetrees and includes a new functionality to automatically predict gene duplication events in gene family trees. The 64-bit Mega is made available in two interfaces: graphical and command line. The graphical user interface (GUI) is a native Microsoft Windows application that can also be used on Mac OS X. The command line Mega is available as native applications for Windows, Linux, and Mac OS X. They are intended for use in high-throughput and scripted analysis. Both versions are available from www.megasoftware.net free of charge.
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            A global reference for human genetic variation

            The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.
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              The complete genome sequence of a Neandertal from the Altai Mountains

              We present a high-quality genome sequence of a Neandertal woman from Siberia. We show that her parents were related at the level of half siblings and that mating among close relatives was common among her recent ancestors. We also sequenced the genome of a Neandertal from the Caucasus to low coverage. An analysis of the relationships and population history of available archaic genomes and 25 present-day human genomes shows that several gene flow events occurred among Neandertals, Denisovans and early modern humans, possibly including gene flow into Denisovans from an unknown archaic group. Thus, interbreeding, albeit of low magnitude, occurred among many hominin groups in the Late Pleistocene. In addition, the high quality Neandertal genome allows us to establish a definitive list of substitutions that became fixed in modern humans after their separation from the ancestors of Neandertals and Denisovans.
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                Author and article information

                Contributors
                Role: Associate Editor
                Journal
                Mol Biol Evol
                Mol Biol Evol
                molbev
                Molecular Biology and Evolution
                Oxford University Press
                0737-4038
                1537-1719
                August 2022
                09 July 2022
                09 July 2022
                : 39
                : 8
                : msac151
                Affiliations
                Departments of Medicine, Pathology, Anthropology and Cellular and Molecular Medicine, Center for Academic Research and Training in Anthropogeny and Glycobiology Research and Training Center, University of California San Diego , San Diego, CA 92093, USA
                Departments of Medicine, Pathology, Anthropology and Cellular and Molecular Medicine, Center for Academic Research and Training in Anthropogeny and Glycobiology Research and Training Center, University of California San Diego , San Diego, CA 92093, USA
                Department of Genetics, Princeton University , Princeton, NJ 08544, USA
                Departments of Medicine, Pathology, Anthropology and Cellular and Molecular Medicine, Center for Academic Research and Training in Anthropogeny and Glycobiology Research and Training Center, University of California San Diego , San Diego, CA 92093, USA
                Departments of Medicine, Pathology, Anthropology and Cellular and Molecular Medicine, Center for Academic Research and Training in Anthropogeny and Glycobiology Research and Training Center, University of California San Diego , San Diego, CA 92093, USA
                Departments of Medicine, Pathology, Anthropology and Cellular and Molecular Medicine, Center for Academic Research and Training in Anthropogeny and Glycobiology Research and Training Center, University of California San Diego , San Diego, CA 92093, USA
                Department of Chemistry, University of California Davis , Davis, CA 95616, USA
                Department of Chemistry, University of California Davis , Davis, CA 95616, USA
                Department of Genetics, Princeton University , Princeton, NJ 08544, USA
                Biognos AB , Gothenburg SE-402 74, Sweden
                Departments of Medicine, Pathology, Anthropology and Cellular and Molecular Medicine, Center for Academic Research and Training in Anthropogeny and Glycobiology Research and Training Center, University of California San Diego , San Diego, CA 92093, USA
                Departments of Medicine, Pathology, Anthropology and Cellular and Molecular Medicine, Center for Academic Research and Training in Anthropogeny and Glycobiology Research and Training Center, University of California San Diego , San Diego, CA 92093, USA
                Author notes
                Corresponding authors: E-mails: a1varki@ 123456ucsd.edu ; pgagneux@ 123456ucsd.edu .
                Author information
                https://orcid.org/0000-0002-2206-975X
                Article
                msac151
                10.1093/molbev/msac151
                9356730
                35809046
                66b27c93-5cad-41f5-9e54-797318c24fef
                © The Author(s) 2022. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                Page count
                Pages: 17
                Funding
                Funded by: National Institute of Health, doi 10.13039/100000002;
                Award ID: R01GM32373
                Funded by: Cure Alzheimer's Fund, doi 10.13039/100007625;
                Categories
                Discoveries
                AcademicSubjects/SCI01130
                AcademicSubjects/SCI01180

                Molecular biology
                cd33,pathogen,sialic acids,archaic genome,molecular dynamics simulation,phylogenetic analysis

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