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. 2020 Apr 30;43(4):331-339.
doi: 10.14348/molcells.2020.2282.

Accelerated Evolution of the Regulatory Sequences of Brain Development in the Human Genome

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Free PMC article

Accelerated Evolution of the Regulatory Sequences of Brain Development in the Human Genome

Kang Seon Lee et al. Mol Cells. .
Free PMC article

Abstract

Genetic modifications in noncoding regulatory regions are likely critical to human evolution. Human-accelerated noncoding elements are highly conserved noncoding regions among vertebrates but have large differences across humans, which implies human-specific regulatory potential. In this study, we found that human-accelerated noncoding elements were frequently coupled with DNase I hypersensitive sites (DHSs), together with monomethylated and trimethylated histone H3 lysine 4, which are active regulatory markers. This coupling was particularly pronounced in fetal brains relative to adult brains, non-brain fetal tissues, and embryonic stem cells. However, fetal brain DHSs were also specifically enriched in deeply conserved sequences, implying coexistence of universal maintenance and human-specific fitness in human brain development. We assessed whether this coexisting pattern was a general one by quantitatively measuring evolutionary rates of DHSs. As a result, fetal brain DHSs showed a mixed but distinct signature of regional conservation and outlier point acceleration as compared to other DHSs. This finding suggests that brain developmental sequences are selectively constrained in general, whereas specific nucleotides are under positive selection or constraint relaxation simultaneously. Hence, we hypothesize that human- or primate-specific changes to universally conserved regulatory codes of brain development may drive the accelerated, and most likely adaptive, evolution of the regulatory network of the human brain.

Keywords: brain evolution; chromatin interaction; fetal brain; human accelerated region; ultra-conserved element.

Conflict of interest statement

CONFLICT OF INTEREST

The authors have no potential conflicts of interest to disclose.

Figures

Fig. 1
Fig. 1. Epigenetic interpretation of pre-defined human-accelerated regions.
(A) The number of HAE overlaps per 104 DHSs in each tissue or cell type. The fetal samples are ordered by the age of the donor (days after conception). P values were derived from two-tailed Student’s t-tests. (B) The number of HAE overlaps per 104 peaks of each histone modification in developing brains (left four) and adult brains. The second and third categories from the left are neurosphere ganglionic eminence-derived (NGED) and neurosphere cortex-derived (NCD) samples, respectively. The zero values for H3K27ac in the first six bars in Fig. 1B do not indicate less overlap, but indicate the lack of data matched to DHSs.
Fig. 2
Fig. 2. Enrichment of evolutionary signatures in DHS sequences.
(A) The frequency of human-accelerated (P < 5.0 × 10-4) nucleotides in the DHSs with different origins (left) compared with that of human-accelerated nucleotides in fetal brain-specific DHS segments, primate-specific accelerated nucleotides, and mammal-specific accelerated nucleotides (right). (B) The number of UCE overlaps per 104.
Fig. 3
Fig. 3. Transcriptional regulation of coexistence of UCE and HAE in fetal brain DHS region.
(A) Chromatin-interaction landscape between a fetal brain DHS containing an HAE and UCE and the promoter of FAXC in dorsolateral prefrontal cortex tissue. Hi-C interaction frequency maps were plotted using the 3DIV database, available at http://kobic.kr/3div/ (Yang et al., 2018). The location of the fetal brain DHS is indicated by the red dot. The green line indicates the cut-off for the distance-normalized interaction frequency. (B) A brain DHS that contains an HAE and UCE simultaneously and that is active only during prenatal periods and early infancy. Shown are the locations of the HAE and UCE, primate phastCons (sky blue) and phyloP (blue for conservation and red for acceleration) scores, SNAI2 and THRB binding motifs, and the frequency of each base among primates with the human reference sequences at the bottom. For the two motifs, THRB was identified as a single motif with statistical significance (P value: 7.0 × 10-7) and SNAI2 showed the highest statistical significance (P value: 4.0 × 10-6 brain development.
Fig. 4
Fig. 4. RPKM expression values for THRB (top) and SNAI2 (bottom) are plotted according to the age of the donor and the sub-region of the brain.
Prenatal and postnatal gene expression values are shown in red and blue, respectively (pcw, post-conception week; mo, months; y, years).
Fig. 5
Fig. 5. Evolutionary patterns of DHS sequences.
(A) Regional conservation (average phastCons score) in the primate clade for the DHSs with different origins. (B) Outlier point acceleration (minimum phyloP score) in the primate clade for the DHSs with different origins. (C) Relative point acceleration (combined phastCons and phyloP scores) in the primate and mammalian clades. All data are represented as mean ± SD; P values were derived from two-tailed Student’s t-tests. **P ≤ 0.0005, ***P ≤ 0.00005.

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