Motifome comparison between modern human, Neanderthal and Denisovan

Abstract

BackgroundThe availability of the genomes of two archaic humans, Neanderthal and Denisovan, and that of modern humans provides researchers an opportunity to investigate genetic differences between these three subspecies on a genome-wide scale. Here we describe an algorithm that predicts statistically significant motifs based on the difference between a given motif’s actual and expected distributions. The algorithm was previously applied to plants but was modified for this work.ResultsThe result of applying the algorithm to the human, Neanderthal, and Denisovan genomes is a catalog of potential regulatory motifs in these three human subspecies. We examined the distributions of these motifs in genetic elements including human retroviruses, human accelerated regions, and human accelerated conserved noncoding sequences regions. Differences in these distributions could be the origin of differences in phenotype between the three subspecies. Twenty significant motifs common to all three genomes were found; thirty-three were found in endogenous retroviruses in Neanderthal and Denisovan. Ten of these motifs mapped to the 22 bp core of MiR-1304. The core of this genetic element regulates the ENAM and AMTN genes, which take part in odontogenesis and whose 3’ UTRs contained significant motifs. The introns of 20 genes were found to contain a large number of significant motifs, which were also overrepresented in 49 human accelerated regions. These genes include NAV2, SorCS2, TRAPPC9, GRID1, PRDM16, CAMTA1, and ASIC which are all involved in neuroregulation. Further analysis of these genes using the GO database indicates that many are associated with neurodevelopment. Also, varying numbers of significant motifs were found to occur in regions of the Neanderthal and Denisovan genomes that are missing from the human genome, suggesting further functional differences between modern and archaic humans.ConclusionAlthough Neanderthal and Denisovan are now extinct, detailed examination of elements from their genomes can shed light on possible phenotypic and cognitive differences between these two archaic human subspecies and modern humans. Genetic similarities and differences between these three subspecies and other fossil hominids would also be of interest.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-4710-1) contains supplementary material, which is available to authorized users.

Modern human alleles differentially regulate gene expression across brain regions: implications for brain evolution

“…Geometric morphometrics studies that compared Homo sapiens and Neanderthals [Bastir et al, 2011, Kochiyama et al, 2018] had already identified that Homo sapiens has significantly larger olfactory bulbs compared to Neanderthals. Cell-cell adhesion also has been found enriched previously in a motif macroanalysis of the Neanderthal and Denisovan genomes [Cserhati et al, 2018]. Cell adhesion is an important process in human-specific cortical folding and apical progenitors cell cycle [Mora-Bermúdez et al, 2016, Wianny et al, 2018].…”

K-mer-Based Motif Analysis in Insect Species across Anopheles, Drosophila, and Glossina Genera and Its Application to Species Classification

“…This is because in the normal distribution, 5% of all values lie above 1.96 z -score limit. This cutoff was also used in the k-mer prediction study of modern and archaic humans [3].…”

“…These elements are both conserved and diverged across species owing to their functional significance, which enables these k-mer signatures ideal for species identification. Several recent studies have described the distribution of statistically significant k-mers in the genomes and several regulatory subregions (core, proximal, distal promoters, and 3′ and 5′ UTRs) in a small number of plant species as well as modern and archaic humans [1–3]. A k-mer is a type of short oligonucleotide of length k. K-mers can be part of core segments of transcription factor binding sites or regulatory elements that take part in protein binding and gene regulation in different subregions of the genome.…”

“…Compared to our previous work in this area [1–3], the current improved algorithm scores k-mer significance based on a normalized scale of −1 to +1, which is used to calculate k-mer signatures so as not only to predict statistically significant and biologically relevant k-mers, but also to make the genomes of two given species comparable based on their k-mer signatures. Therefore, the goal of this study is to further develop a k-mer prediction method, which can be used to predict biologically significant k-mers and then to use these k-mers in species comparison and clustering.…”

Bioinformatics for Plant Genetics and Breeding Research

“…A k-mer is unique sub-sequence of nucleotide sequence. The distribution of statistically significant kmers in a genomes and other regulatory subregions has been described in a number of recent studies (Hashim and Abdullah 2015;Cserhati et al 2018). It has also been also employed in comparative studies (Cserhati et al 2019), and major advantages of alignment-free approaches based on k-mer are their speed and ability to remove biases.…”