Selected neuropeptide genes show genetic differentiation between Africans and non-Africans.

BACKGROUND: Publicly available genome data provides valuable information on the genetic variation patterns across different modern human populations. Neuropeptide genes are crucial to the nervous, immune, endocrine system, and physiological homeostasis as they play an essential role in communicating information in neuronal functions. It remains unclear how evolutionary forces, such as natural selection and random genetic drift, have affected neuropeptide genes among human populations. To date, there are over 100 known human neuropeptides from the over 1000 predicted peptides encoded in the genome. The purpose of this study is to analyze and explore the genetic variation in continental human populations across all known neuropeptide genes by examining highly differentiated SNPs between African and non-African populations.
RESULTS: We identified a total of 644,225 SNPs in 131 neuropeptide genes in 6 worldwide population groups from a public database. Of these, 5163 SNPs that had ΔDAF |(African - non-African)| ≥ 0.20 were identified and fully annotated. A total of 20 outlier SNPs that included 19 missense SNPs with a moderate impact and one stop lost SNP with high impact, were identified in 16 neuropeptide genes. Our results indicate that an overall strong population differentiation was observed in the non-African populations that had a higher derived allele frequency for 15/20 of those SNPs. Highly differentiated SNPs in four genes were particularly striking: NPPA (rs5065) with high impact stop lost variant; CHGB (rs6085324, rs236150, rs236152, rs742710 and rs742711) with multiple moderate impact missense variants; IGF2 (rs10770125) and INS (rs3842753) with moderate impact missense variants that are in linkage disequilibrium. Phenotype and disease associations of these differentiated SNPs indicated their association with hypertension and diabetes and highlighted the pleiotropic effects of these neuropeptides and their role in maintaining physiological homeostasis in humans.
CONCLUSIONS: We compiled a list of 131 human neuropeptide genes from multiple databases and literature survey. We detect significant population differentiation in the derived allele frequencies of variants in several neuropeptide genes in African and non-African populations. The results highlights SNPs in these genes that may also contribute to population disparities in prevalence of diseases such as hypertension and diabetes.

Background

Neuropeptide genes [1, 2] are no different when it comes to genetic risk. As their name indicates, these genes code for neuropeptides are peptide molecules that are synthesized and released from nerve cells in the brain and act either at the local level in the brain or affect distant organs. For more than 30 years following the discovery of the first neuropeptide by Van Euler in 1931, studies [3] were geared towards the role of these peptides as signaling molecules in the peripheral and central nervous systems, where they act as fine tuners of neurotransmissions that control the balance between neuronal inhibition and excitation. A large number of neuropeptides were identified during this period [4, 5].

Neuropeptides are also expressed in the endocrine and immune system and play a major role in physiological homeostasis. They intersect the immune, nervous and endocrine systems through autocrine, neurocrine, paracrine and endocrine manners, thus playing a core role in influencing postsynaptic cells in a large target area [6]. In physiological homeostasis, neuropeptides act as peptide hormones regulating functions such as feeding behavior, reproduction, stress response, energy homeostasis, cognition, pain and blood pressure. Additionally, they perform their physiological processes by binding to corresponding receptors [7] and an abundance of neuropeptides has been reported in almost every system of the human body [4, 6, 8]. To date, from over 1000 predicted peptides encoded in the human genome, there are now over 100 known neuropeptide genes in the human and undoubtedly many more that are yet to be identified and annotated [9].

As humans migrated into new frontiers outside Africa their populations became fragmented and genetically differentiated. This genetic diversity can also be a source of differences in genetic risk for particular ailments between different populations. For example, variant rs2478523 in the AGT gene shows an increase in the risk of high altitude polycythemia (HAPC) in the Tibetan population while in the Han population, rs699, rs4762 and rs5051 are associated with reduced HAPC susceptibility [10]. Also, in the USA population, a minor allele rs5065 in NPPA was identified as a marker of increased cardiovascular risk [11], and in the North Indian population, rs1042571 in POMC was shown to increase the risk of obesity [12]. Due to the importance of neuropeptides, even minor variations in neuropeptide genetic structure can lead to vastly different physiological effects. Differences in neuropeptide genetics can thus serve as better markers or indicators for the susceptibility of a specific population for certain diseases, aiding in population health measures. Even so, the knowledge available on the variability and expression pattern of these neuropeptide genes in different modern human populations is limited at the moment. The majority of the studies conducted on these genes [13-15] so far have tended to focus on one specific neuropeptide in one specific population [11, 16–19].

The rapid development in sequencing technology and decreasing costs of genome sequencing now proffer an unbiased examination of human genetic variation and have led to the development of several large scale human whole exome and whole genome databases, such as the 1000 Genomes Project [20], the Trans-Omics for Precision Medicine (TOPMed) and the Genome Aggregation Database Consortium [21], that aim to translate these gains into clinical medical practice based on personalized genomics. The major goal of these projects is to establish a comprehensive catalogue of all detectable variations, which is essential for characterizing human genetic diversity as well as identifying risk variants associated with human diseases. By being able to monitor the variations in multiple genes simultaneously in a particular population and forming a genomic profile, it is possible to deduce their influence on a disease, or even overall health.

In this study, we analyzed the genetic variation in continental human populations across known neuropeptide genes. In particular, we examined single nucleotide polymorphisms (SNP) that were highly differentiated between African and non-African populations in publicly available datasets, to gain insights about the patterns of genetic variations in genes that code for neuropeptides and examine whether any are undergoing any adaptive selection in these populations.

Results

Human neuropeptide genes

A total of 105 neuropeptide genes were identified from four neuropeptide databases; StraPep [22], neuropeptides.nl [23], NeuroPedia [24] and NeuroPep [25], by using the search term “Homo sapiens”. An additional 26 neuropeptide genes were identified by Ensembl [26] and AmiGO Gene Ontology [27]. Therefore, the final list comprised of 131 human neuropeptide genes (Fig. 1, Additional file 1: Table S1).

Fig. 1

Human neuropeptide genes obtained from the online database and literature survey

Variation in neuropeptide genes

Using the whole genome sequence data, we extracted variants for the 131 neuropeptide genes in 15,164 individuals belonging to 6 different populations, Africans, Latino, Ashkenazi Jewish, East Asian, Finnish and Non-Finnish Europeans. A total of 769,597 variable sites were identified in the 131 neuropeptide genes (Additional file 2: Table S2). We filtered out 125,372 indels variants and retained a total number of 644,225 SNPs for downstream analysis because ancestral alleles could not be obtained for the indels.

Highly differentiated SNPs in Africans and non-Africans

SNPs in neuropeptide genes, that had absolute differences in derived allele frequencies (DAF) between African and non-African populations equal to or more than 0.20, were identified and functionally annotated (Figs. 2 and 3). A cutoff point of DAF ≥ 0.20 was selected because it represented the extreme (< 1%) outliers amongst the 644,225 SNPs (Additional file 3: Figure S1). Overall, 5163 of 644,225 SNPs met this criteria (Additional file 4: Table S3). Ensembl Variant Effect Predictor (VEP) tool was used to annotate these 5163 SNPs to identify missense variants or SNPs with high impact functional consequences (Additional file 5: Figure S2). A total of 20 SNPs (Table 1), that included 19 moderate impact missense SNPs and one high impact loss of stop codon, were identified in 16 different neuropeptide genes. An overall strong population differentiation was observed in the non-African populations that had a higher derived allele frequency for 15/20 of these SNPs.

Fig. 2

Proportion of SNPs binned on basis of the absolute differences in African and non-African derived allele frequencies (ΔDAF). Numbers inside and outside the bars refer to the proportion of SNPs that were observed in each bin

Fig. 3

Proportion of neuropeptide gene SNPs in various derived allele frequency bins in African and non-African populations

Table 1

Twenty SNPs in neuropeptide genes that are highly differentiated between Africans and non-Africans

SNP ID	Chromosome	HGNC Symbol	Ref	Ancestor	Derived	ΔDAF |(African - non-African)|	Feature keya (Position)	FST YRI vs CEU	FST YRI vs CHB	eQTL (↓decrease; ↑increase)
rs3842753	11	INS	T	T	G	0.50		0.44	0.70	TH↑; IGF2-AS↓; IGF2↑
rs3847193	9	QRFP	G	A	G	0.42	Propeptide (19–90)	0.34	0.68	QRFP↓; FIBCD1↑
rs2291725	17	GIP	T	T	C	0.38	Propeptide (95–153)	0.49	0.64	AC091133.1↓; ATP5G1↑; ATP5G1↓; CDK5RAP3↑; HOXB-AS1↑; HOXB2↑; SNF8↑; SUMO2P17↑; TTLL6↓; UBE2Z↑; UBE2Z↓
rs699	1	AGT	A	G	A	0.36		0.46	0.07	AGT↑; AGT↓; COG2↑
rs6788319	3	UTS2B	C	T	A	0.34	Signal peptide (1–28)	0.27	0.22	UTS2B↓; UTS2B↑; CCDC50↓; OSTN-AS1↑
rs10770125	11	IGF2	A	A	G	0.32		0.30	0.21	IGF2-AS↓
rs5065	1	NPPA	A	G	A	0.30		0.16	0.42	CLCN6↑; MTHFR↑; NPPA↑; NPPA-AS1↑
rs2286472	16	NPW	A	C	A	0.29	Propeptide (65–165)	0.17	0.18	NPW↓; RP11-304 L19.13↑; SLC9A3R2↑; SYNGR3↑
rs1885137	14	SERPINA11	T	T	G	0.28		0.36	0.09	RP11-349I1.2↓; SERPINA11↓
rs7121	20	GNAS	C	T	C	0.28		0.35	0.12	GNAS↑; CTSZ↑
rs757081	11	NUCB2	C	C	G	0.26		0.39	0.40	RP1-239B22.5↓; PIK3C2A↓; OR7E14P↓; NUCB2↓; NCR3LG1↓; KCNJ11↓
rs990310	10	NPS	C	C	T	0.24	Signal peptide (1–23)	0.30	0.32
rs742711	20	CHGB	G	G	A	0.21		0.13	0.19	KANK1P1↑; CHGB↑
rs236152	20	CHGB	C	C	G	0.21		0.13	0.02	CHGB↑; KANK1P1↑; LRRN4↓; MCM8↓; RP5-1056H1.2↑
rs6085324	20	CHGB	T	T	A	0.21		0.13	0.19	KANK1P1↑; CHGB↑;
rs1799917	16	GNAO1	A	G	A	0.21		0.10	0.28	AMFR↑; AMFR↓; BBS2↑; RP11-413H22.3↓
rs236150	20	CHGB	G	G	C	0.21	O-glycosylated (116–120)	0.22	0.22
rs34123523	16	AGRP	C	C	T	0.21	Propeptide (21–82)	0.16	0.21
rs1058046	17	PYY	G	G	C	0.20	Propeptide (68–97)	0.11	0.05	PYY↓
rs742710	20	CHGB	C	C	T	0.20		0.21	0.02

aFeature key refer to the Post-translational modifications (PTM) events in the protein and position refer to the PTM events position in the protein

Genes of interest

Twenty SNPs that were highly differentiated (ΔDAF ≥0.20) between Africans and non-Africans occurred in 16 of 131 neuropeptide genes. Their functional consequences were analyzed using available phenotype data in Genome Wide Association Studies (GWAS) catalogue [28], Online Mendelian Inheritance in Man (OMIM) [29] and gene expression data from Genotype-Tissue Expression (GTEx) portal [30] (Table 1). Median-joining haplotype networks were constructed for these SNPs to investigate the relationship between the African and non-African haplotypes (Additional file 6: Figure S3). To compare how unusual these haplotype networks were we also generated networks for genomic regions where no SNPs had ΔDAF ≥0.20. (Additional file 7: Figure S4). As expected there were no high frequency population specific haplotypes.

Variants in four of these genes (NPPA, CHGB, IGF2 and INS) were especially striking because of the following salient features: NPPA with a high impact stop lost variant (rs5065); CHGB with multiple moderate impact missense variants (rs6085324, rs236150, rs236152, rs742710 and rs742711); IGF2 (rs10770125) and INS (rs3842753) with moderate impact missense variants that are in linkage disequilibrium. These variants are further examined in the following sections.

NPPA

The SNP (rs5065) in NPPA has been associated with cardiovascular disease risk [11, 31] and acute coronary syndrome [32]. The derived allele frequency is significantly higher in non-Africans (88%) as opposed to Africans (59%). A haplotype network based upon 94 SNPs in a 2 kb genomic region encompassing NPPA (Fig. 4) clearly shows rs5065 on the branch separating two main haplotypes, one comprising mostly of African haplotypes with frequency of 0.20 and the other including all continental groups with frequency of 0.72.

Fig. 4

NCBI RefSeq and UniProt annotations track with haplotype network showing a 2 kb region encompassing NPPA in Africans (YRI), East Asians (CHB) and Europeans (CEU)

CHGB

Five highly differentiated SNPs occurred in the CHGB gene (rs6085324, rs236150, rs236152, rs742710 and rs742711). Three of these SNPs (rs236150, rs236152 and rs742710) had a high derived allele frequency in African populations and two SNPs (rs6085324 and rs742711) in non-Africans (Table 2). All five SNPs were associated with stress that arises due to changes in blood pressure in Southern Californians, including sub-Saharan African and European ancestry groups [33]. Moreover, two SNPs (rs6085324 and rs742711) have been associated with schizophrenia in the Korean population [19] and SNP rs236152 has also been associated with schizophrenia in the Japanese population [16].

Table 2

Derived allele frequencies of highly differentiated SNPs in CHGB in Africans and non-Africans

SNP ID	African DerivedAllele Frequency	non-African Derived Allele Frequency	ΔDAF |(African - non-African)|
rs6085324	0.1075	0.3187	0.2112
rs236150	0.2102	0.0019	0.2083
rs236152	0.6309	0.4176	0.2133
rs742710	0.2513	0.0506	0.2007
rs742711	0.1045	0.3184	0.2140

The relationship between these 5 SNPs was further explored by using Africans and non-Africans allele linkage disequilibrium (LD) (Table 3). A median-joining haplotype network was constructed using 1000 Genomes Project continental populations representing Africans, East Asians and Europeans [20]. Two haplotype networks were constructed, one consisting of 411 SNPs from the whole CHGB 14 kb genomic region (Additional file 8: Figure S5) and another comprising of 57 SNPs (including the 5 highly differentiated variants) in a 1 kb region of CHGB exon 4 (Fig. 5a-b). The haplotype network shows that four SNPs, including three of the five highly differentiated ones (rs236152, rs6085324 and rs742711), separate the two major haplotypes, whereas the remaining 2 SNPs (rs236150 and rs742710) mainly separate other Africans and minor non-Africans haplotypes from one another.

Table 3

Pairwise linkage disequilibrium (LD) between five highly differentiated CHGB SNPs in Africans (above diagonal) and non-Africans (below diagonal)

SNP ID	rs6085324	rs236150	rs236152	rs742710	rs742711
rs6085324		0.022	0.040	0.030	1
rs236150	0.020		0.156	0.102	0.022
rs236152	0.502	0.054		0.214	0.040
rs742710	0.057	0.006	0.153		0.030
rs742711	1	0.020	0.502	0.057

Fig. 5

Genomic region and haplotypes for CHGB. a NCBI RefSeq and UniProt annotations track for a 14 kb genomic region on chromosome 20 encompassing the CHGB gene. The location of the five highly differentiated SNPs is shown above the exon (blue box). b NCBI RefSeq and UniProt annotations track with haplotype network of a 1 kb exonic region containing the highly differentiated SNPs within CHGB exon 4 in Africans (YRI), East Asians (CHB) and Europeans (CEU)

IGF2 and INS

The SNP (rs10770125) in IGF2 and (rs3842753) in INS are located close together on chromosome 11. GTEx data shows that IGF2 is highly expressed in the Adipose – Visceral (Omentum) and INS is highly expressed in the pancreas. The derived allele frequencies of both SNPs are higher in non-Africans as compared to Africans (Table 4). The relationship between these 2 SNPs was further studied using LD and haplotype network. The result show a higher LD in Africans (r2 = 0.336) than in non-Africans (r2 = 0.056). A haplotype network based upon 65 SNPs in a 1 kb genomic region of IGF2 (Additional file 9: Figure S6) and a haplotype network based upon 66 SNPs in a 1 kb genomic region of INS (Additional file 10: Figure S7) were constructed. As expected, in both networks non-Africans exhibit high frequency haplotypes that have derived alleles for both these SNPs. A study [34] linked rs3842753 to improved identification of atypical Type 2 Diabetes (T2D) patients in the Uruguayan population of predominantly European ancestry. In a separate study of European American descents in the GoKinD project [35], IGF2 rs10770125 has been associated with diabetic nephropathy in male patients with T1D, but not in female patients [36].

Table 4

Derived allele frequencies and ΔDAF for highly differentiated SNPs in IGF2 and INS in Africans and non-Africans

SNP ID	African DerivedAllele Frequency	non-African Derived Allele Frequency	ΔDAF |(African - non-African)|
rs10770125	0.1750	0.4979	0.3229
rs3842753	0.2568	0.7581	0.5013

Discussion

We used genome sequence data from six different populations groups in the Genome Aggregation Database (gnomAD) to extract variants for 131 neuropeptide genes. Using differences in derived allele frequencies we identified 20 highly differentiated SNPs between Africans and non-African populations in 16 neuropeptide genes (Table 1). Functional analysis of these highlighted the pleiotropic effects of these neuropeptide genes and their association with complex diseases such as hypertension and diabetes, the prevalence of which is known to differ between individuals of African and European ancestry [33, 34].

The high impact stop lost variant (rs5065) in NPPA has been associated with increased acute coronary syndrome [32] and cardiovascular risk [11, 31]. NPPA encodes a protein implicated in the control of extracellular fluid volume and electrolyte homeostasis and is highly expressed by the heart muscle. Furthermore, the ventricular expression of this gene is strongly increased in the cardiac muscle cells of the mice during stress [37].

A number of these highly differentiated SNPs were in genes that help regulate the amount of intracellular calcium that is known to play a crucial role in the regulation of cardiovascular functions. An increase in calcium in vascular smooth muscle cells leads to an augmented muscular tone which further increases vascular resistance that eventually raises the blood pressure [38]. One such gene is CHGB [39] that stimulates catecholamine secretion [40]. Common genetic variation at the CHGB locus, especially in the proximal promoter, influences CHGB expression, catecholamine secretion and the early heritable responses to environmental stress and is associated with changes in blood pressure in the sub-Saharan African and European ancestry groups [33]. Five missense variants (rs6085324, rs236150, rs236152, rs742710 and rs742711) that lie in a single exon have high ΔDAF between Africans and non-Africans and three (rs236152, rs742711 and rs6085324) of these (Table 1) are associated with increased CHGB expression in the GTEx dataset [30]. Of these three SNPs one (rs236152) has a higher derived allele frequency (63%) in Africans. Another close SNP (rs236150) that also has a higher derived allele frequency (21%) in Africans is also predicted to be differentially O-glycosylated. Another calcium binding protein with a highly differentiated SNP (rs757081) was NUCB2. NUCB2 shares a 60% sequence homology with NUCB1 in the human and mouse genome [41] and plays an important role in homeostatic functions associated with stress response [42], where its expression increased intracellular calcium concentration by protein kinase C activation in cultured rat cultured rat dorsal root ganglion neurons [43]. This SNP has also been associated with systolic blood pressure, mean arterial pressure and pulse pressure in individuals with European ancestry [44], and in African Americans it has been associated with both systolic and diastolic blood pressure [45]. AGT, another gene with a highly differentiated SNP, rs699, with a derived allele frequency of 17% in Africans, has also been associated with hypertension in African populations [46]. Based on the single-tissue eQTL in GTEx, the NUCB2 rs757081 and AGT rs699 decreases their gene expression levels in several tissues and both SNPs have been associated with hypertension in the GWAS catalogue [28].

Several of the other genes, including INS, GIP and IGF2 with highly differentiated SNPs are involved in regulating glucose homeostasis. Evidence from epidemiological studies suggests that African Americans are also more insulin resistant and have higher insulin responses to glucose than European Americans [47]. The balance between insulin and glucagon levels is crucial in maintaining glucose homeostasis [48]. INS rs3842753 with a derived allele frequency of more than 75% in non-African populations has been identified as a marker for atypical T2D in the Uruguayan population [34], while IGF2 rs10770125 has been associated with diabetic nephropathy in people with European American ancestry [36]. GIP is secreted from K cells and acts on pancreatic beta cells to stimulate the release of insulin. Using the HGDP-CEPH project and the Human Genome Center at the University of Tokyo datasets, a previous study [49] showed that the derived frequency of rs2291725 is significantly higher (> 60%) in the majority of East Asian populations while varying widely in other populations, ranging between 0.0–9.5% in sub-Saharan Africans and increasing to > 40% in European and Middle Eastern populations. We also noted a low derived allele frequency of 14% for this SNP in the Africans and a significantly higher derived allele frequency of 52% for non-Africans. The highest derived allele frequency was also seen in East Asian populations with frequency of 0.75. NUCB2 rs757081 variant was also associated with the decreased risk of developing T2D in Chinese Han population [50]. The CHGB gene is also essential for adequate secretion of islet hormones in mice, where its deficiency led to a phenotype with some hallmarks of human T2D including loss of initial rapid insulin secretion [51]. Three missense variants (rs6085324, rs742711 and rs236152) have been associated with schizophrenia and increased risk for T2D [19].

A major limitation of the study was the non-availability of individual sequences in the gnomAD dataset. Therefore, selected sequences from the 1000 Genomes Project continental populations representing Africans and non-Africans were used to construct the haplotype networks, compute LD and FST for the highly differentiated SNPs. As expected haplotype networks for the highly differentiated genes show population sub-structure with high frequency population specific haplotypes. However, this could not be considered an unusual feature, because it is dependent upon the underlying linkage disequilibrium between SNPs in these populations and confounded by selection and demography.

Conclusions

Our study shows substantial population differentiation between African and non-African, as measured by differences in derived allele frequencies, in variants located in 131 neuropeptide genes. Twenty outlier SNPs with ΔDAF |(African – non-African)| ≥ 0.20 were identified in 16 neuropeptide genes and their functional significance was evaluated. The product of these genes appeared to affect multiple systems and some were associated with ethnic differences in incidence of common human diseases such as high blood pressure and type 2 diabetes. Significantly, our analysis adds to our knowledge of the genetic variation in continental human populations across all known neuropeptide genes. It also highlights the pleiotropic nature of these neuropeptides, their functional significance in extra neuronal tissues and their association with cardiovascular and metabolic diseases.

Methods

Data sets

A list of human neuropeptide genes was manually generated by integrating information from neuropeptide databases, Ensembl, and AmiGO Gene Ontology. Four neuropeptide databases were used for obtaining the gene list and included: StraPep [22], neuropeptides.nl [23], NeuroPedia [24] and NeuroPep [25]. This primary gene list was generated by using the search term “Homo sapiens”. The list was further refined by adding more neuropeptide genes using the search term “Neuropeptide” in Homo sapiens in Ensembl (Ensembl GRCh37.p13) [26] and AmiGO Gene Ontology [27]. In addition, for AmiGO the following GO terms were also used:

Gene ontology - Molecular function

GO:0005184 neuropeptide hormone activity

GO:0051428 peptide hormone receptor binding

GO:0071855 neuropeptide receptor binding

Gene ontology - Biological process

GO:0007218 neuropeptide signaling pathway

The final list comprised a total of 131 human neuropeptide genes (Fig. 1, Additional file 1: Table S1).

Whole genome sequence data were obtained from a total of 15,164 genomes from gnomAD [21]. This dataset comprises of 6 different populations, Africans (including African Americans), Latino, Ashkenazi Jewish, East Asian, Finnish and Non-Finnish European (Additional file 11: Table S4), which were sequenced between 20 to 30X depth of coverage.

Genetic diversity

The genetic differences between the African and non-African populations in the gnomAD sequence dataset were characterized using SNPs. The ancestral states of each SNP were determined by the Ensembl Biomart tools [52]. If the ancestral state of the SNP was not provided in Ensembl, a comparison between the allele with the primates using Ensembl multiple primate’s alignment was performed, and the consensus primate allele was used as the ancestral allele for that SNP. Based on the ancestral state, derived allele frequency was tabulated for each SNP and absolute differences of the ΔDAF between African and non-African populations were estimated.

Functional annotations of selected genes

SNPs were filtered by ΔDAF |(African - non-African)| ≥ 0.20, as this was above the 99th percentile of the distribution. All outlier SNPs were functionally annotated using the VEP tool [53] to determine the most severe consequence for each variant. The primary interest was to see if there were any highly differentiated missense variants or SNPs with high impact consequences. Selected neuropeptide genes in which ΔDAF |(African - non-African)| ≥ 0.20 were further explored with GeneCards [54] database to retrieve information and related function of the selected genes. In addition, genes with these highly differentiated SNPs were also characterized by their presence in human disease databases such as the OMIM [29] and GWAS catalogue [28] to understand the implication of these functional consequences. Furthermore, GTEx portal [30] was also used to explore whether any of these variants affected the level of neuropeptide genes in different tissues.

Haplotype networks

Median-joining haplotype networks were constructed for selected genomic regions using the NETWORK software (version 5) package [55], to investigate the relationship between the African and non-African haplotypes. Due to the non-availability of individual sequences in the gnomAD dataset, all samples from three representative continental 1000 Genomes Project populations [20], that were whole genome sequenced at low coverage (Mean 7.6X), were used to construct the haplotype networks. For this purpose, we used a total of 620 individuals representing 3 major continental populations. These included 216 Yoruba in Ibadan (YRI), 206 Han Chinese in Beijing (CHB) and 198 Utah Residents (CEPH) with Northern and Western European Ancestry (CEU), representing African, East Asian and European continental populations, respectively. The window sizes of the haplotype networks were selected based on pairwise LD values of r2 ≤ 0.2 between the most differentiated and other SNPs in the region (Additional file 12: Table S5). Besides, FST was also calculated for these highly differentiated SNPs using the 1000 Genomes Project YRI, CHB and CEU samples (Table 1).

Additional file 1 : Table S1. List of 131 neuropeptide genes in human.

Additional file 2 : Table S2. General information on the variants data for 131 neuropeptide genes.

Additional file 3 : Figure S1. Distribution of ΔDAF values between Africans and non-Africans.

Additional file 4 : Table S3. SNPs with absolute differences in derived allele frequencies between African and non-African population equal to or more than 0.20. The data are sorted by differences of derived allele frequency.

Additional file 5 : Figure S2. Annotating 5163 SNPs consequences using the Ensembl Variant Effect Predictor (VEP) tool.

Additional file 6 : Figure S3. Median-joining haplotype networks for SNPs listed in Table 1.

Additional file 7 : Figure S4. Median-joining haplotype networks for selected genomic regions in Africans (YRI) and non-Africans (CEU + CHB). A). Five kb region encompassing INS rs3842753 (average ΔDAF = 0.097 for all SNPs in the region). B). Another 5 kb region on the same chromosome 11 where ΔDAF = 0.012 between Africans and non-Africans. Both these genomic regions do not have any SNPs with ΔDAF ≥0.20.

Additional file 8 : Figure S5. Haplotype network of a 14 kb region encompassing CHGB in Africans (YRI), East Asians (CHB) and Europeans (CEU).

Additional file 9 : Figure S6. Haplotype network of a 1 kb region encompassing IGF2 in Africans (YRI), East Asians (CHB) and Europeans (CEU).

Additional file 10 : Figure S7. Haplotype network of a 1 kb region encompassing INS in Africans (YRI), East Asians (CHB) and Europeans (CEU).

Additional file 11 : Table S4. Analyzed populations and samples. Populations were split into two categories. Sample size indicates the number of individuals for each population.

Additional file 12 : Table S5. LD patterns in Africans and non-Africans for highly differentiated SNPs listed in Table 1.