Significant abundance of cis configurations of mutations in diploid human genomes

To fully understand human genetic variation, one must assess the specific distribution of variants between the two chromosomal homologues of genes, and any functional units of interest, as the phase of variants can significantly impact gene function and phenotype. To this end, we have systematically analyzed 18,121 autosomal protein-coding genes in 1,092 statistically phased genomes from the 1000 Genomes Project, and an unprecedented number of 184 experimentally phased genomes from the Personal Genome Project. Here we show that mutations predicted to functionally alter the protein, and coding variants as a whole, are not randomly distributed between the two homologues of a gene, but do occur significantly more frequently in cis-than trans-configurations, with cis/trans ratios of ∼60:40. Significant cis-abundance was observed in virtually all individual genomes in all populations. Nearly all variable genes exhibited either cis, or trans configurations of protein-altering mutations in significant excess, allowing distinction of cis- and trans-abundant genes. These common patterns of phase were largely constituted by a shared, global set of phase-sensitive genes. We show significant enrichment of this global set with gene sets indicating its involvement in adaptation and evolution. Moreover, cis- and trans-abundant genes were found functionally distinguishable, and exhibited strikingly different distributional patterns of protein-altering mutations. This work establishes common patterns of phase as key characteristics of diploid human exomes and provides evidence for their potential functional significance. Thus, it highlights the importance of phase for the interpretation of protein-coding genetic variation, challenging the current conceptual and functional interpretation of autosomal genes.


Introduction
The analysis of human genetic variation has focused so far on the identification, cataloguing and annotation of variants, particularly in protein-coding genes (Abecasis et al. 2012;Lek et al. 2016).
One key aspect of genetic variation has, however, not yet been fully addressed: the distribution of variants between the two homologous chromosomes in a diploid genome. Whether variants reside on the same homologue, in cis, or on both homologues, in trans, is "key to understanding their impact on gene function and phenotype" (Suk et al. 2011;Tewhey et al. 2011). For example, while two null mutations in cis leave the second form of the gene intact, no functional form of the gene is present in a trans configuration, changing phenotype entirely (Benzer 1957). Thus, to fully understand the biology of genes and genomes, the phase of mutations must be known. In a first population level analysis of haplotype-resolved genomes (Hoehe et al. 2014), we have shown nonrandom distribution of mutations between homologous gene forms, as indicated by significant abundance of cis configurations with an average cis/trans ratio of approximately 60:40. This raises the question: Could cis-abundance of mutations, the preferential location of mutations on the same chromosomal homologue of an autosomal gene, represent a key characteristic of diploid human genomes? And if so, which types of genes constitute such phase imbalance? Thus, we aimed to (i) assess the distribution of mutations between protein-coding homologous gene forms in substantially larger numbers of genomes and different population samples, (ii) determine, significant abundance of cis configurations given, the types of genes underlying this phenomenon and (iii) uncover potential biological implications of phase imbalance.
We assessed the cis/trans ratios of mutations in 1,092 statistically haplotype-resolved genomes from the 1000 Genomes database (Abecasis et al. 2012) and each of the different populations contained therein separately. Because the analysis of molecularly and statistically haplotype-resolved genomes had yielded nearly identical results earlier (Hoehe et al. 2014), the use of this large resource appeared suitable. The key results obtained from this resource were then cross-validated in an independent sample of 184 experimentally phased genomes from the Personal Genome Project (PGP) (Mao et al. 2016;Ball et al. 2012), a huge advance over the recent population-level analysis of 14 molecularly haplotype-resolved genomes (Hoehe et al. 2014). Cis/trans ratios were assessed for population samples as a whole as well as for each individual genome separately as described in more detail in Box 1, which also provides further information on the concepts underlying our approach.
The ratios were determined for mutations predicted to alter protein function (the term "proteinaltering" is used synonymously in text), the entirety of amino acid (AA) exchanges and synonymous SNPs (sSNPs), and the combinations of these as they co-occur within the genes. Significant abundance of cis configurations evident, the cis/trans ratios were dissected further per number of variants in a configuration, and the observed ratios compared to the theoretically expected ratios to estimate cis excess. To explain this phenomenon, we examined evidence for ancestral admixture as a potential underlying mechanism. To address the functional implications of this phenomenon, we focused on the genes that had ≥ 2 mutations predicted to functionally alter the protein in either cis, or trans configurations. The fractions of these genes being highly similar between the genomes, we demonstrated existence of a shared, global set of phase-sensitive genes. Testing the genes in this set subsequently for significant excess of either cis or trans configurations unveiled a larger group of cisand smaller group of trans-abundant genes, resulting in observed cis/trans ratio of about 60:40 as the net effect. These two categories of genes were further functionally differentiated by gene ontology (GO) and pathway analysis, and characterized by different mutational architectures of their phase configurations with potential implications for protein structure. Thus, the distinction of cis and trans configurations ultimately leads to the classification of variable autosomal genes into two major, potentially functionally divergent, categories. This work provides a first phase-informed global view of the diploid human exome, highlighting the importance of phase for the interpretation of proteincoding genetic variation, with implications for the conceptual and functional interpretation of autosomal genes. Scheme 2 provides an overview of all different cis and trans configurations expected to occur in a population, if the mutations (2 on the left, 3 on the right) in a protein-coding gene are distributed randomly between the maternal (m) and paternal (p) homologues. The number of different configurations for a defined number of n variants is 2 n ; as illustrated in Scheme 2, for n=2 mutations, 4 different configurations would be expected, and for n=3 mutations, 8 configurations. Evidently, the same configuration type, i.e. distribution pattern, always occurs twice, with the parental origin interchanged, so these two should be biologically equivalent. Because current approaches to haplotyping do not allow distinction of maternal and paternal homologues, the maternal and paternal haplotypes are being collapsed into 'Haplotype 1' and 'Haplotype 2'. Thus, in practice, we score a cis configuration, or any specific type of a trans configuration basically twice, leaving the relative fractions of cis and trans configurations constant. A cis configuration is scored, if 'Haplotype 1' has either solely '1's or '0's; if this is not the case, a trans configuration is scored. If the chance for every variant in a gene to occur on either homologue is equal, the expected fraction of cis configurations is calculated as 1/2 n-1 , n being the number of variants. Obviously (see also Scheme 2), independently of the number of variants, there will always be 2 cis configurations, while the fraction of trans configurations grows exponentially (Graph).

cis trans trans
Cis/Trans configuration probabilities under random assumptions in relation to the number of variants. Cis fraction: blue; trans fraction: red. Dashed lines refer to the observed composite cis/trans ratio of 60:40.
Notably, for calculation of significance values, we have taken into account that the probability to occur in cis by chance decreases with increasing numbers of variants in a gene (Methods; see also later chapter). Cis-abundance of protein-altering mutations was also evident when analyzing each of the 14 populations that were contained in the 1,092 genomes, with their cis/trans ratios being nearly identical with the median of their respective ancestry groups, with the exception of population ASW in AFR, its cis fraction of 56.3% slightly exceeding the AFR median (Supplemental Table S1). When  Abecasis et al. (2012); 184 experimentally haplotype-resolved genomes from the Personal Genome Project (PGP) described by Mao et al. (2016). 2 Mutations predicted to alter the protein, 'protein-altering mutations', from 1000G annotation database (Abecasis et al. 2012), or annotated using a combination of PolyPhen-2 (Adzhubei et al. 2010), SIFT (Ng and Henikoff 2001) and GERP conservation scores (Cooper et al. 2005) in the PGP genomes.
3 Values represent the median of cis fractions (%), i.e. the number of cis configurations divided by total configuration count per genome across the genomes. 4 Analogous to 3) , trans fractions (%) being 100% -cis fractions (%). 5 Exact Binomial test (see Methods; Hoehe et al. 2014); cis counts were tested against the null hypothesis with a (composite) probability P = 0.4 for a cis configuration. 6 Amino acid (AA) exchanges from 1000G annotation database (Abecasis et al. 2012), or the PGP database, respectively. 7 Synonymous SNPs from 1000G or PGP database. Configs, configurations; p-a, protein-altering; mut, mutations, AA exch, amino acid exchanges analyses were expanded to include the entirety of AA exchanges and sSNPs, the results were once more highly congruent (Supplemental Table S1). Importantly, significant cis-abundance was crossvalidated by the analysis of the 184 experimentally haplotype-resolved PGP genomes (Methods), with nearly identical ratios of 60.4% to 39.6% (P < 1.66×10 -16 ) for protein-altering mutations (Methods), and ratios of 63% to 37% (P < 4.37×10 -51 ) and 65.1% to 34.9% (P < 7.80×10 -70 ), respectively, for the totals of AA exchanges and sSNPs (Table 1). In sum, these results show that protein-altering mutations, and coding variants as a whole, are in effect not distributed randomly between the two homologues of a gene, but do occur significantly more frequently on one of the two gene forms. On average, approximately 60% of the mutated autosomal genes in each genome have their coding variants in cis, and approximately 40% in trans.

More cis than trans configurations in virtually all individual genomes
Inspecting the 1,092 genomes individually, in fact, 99.7% of the 1,092 genomes exhibited more cis than trans configurations of protein-altering mutations. Individual cis fractions varied within a limited range, between 55.7 and 67.1% in EUR and at most between 52.5 and 67.4% in AMR (Fig. 1A).
Inspecting AFR, individual cis fractions were between 49.7 and 63.1%, with nearly half exceeding 55%. Testing each of the 1,092 genomes for statistical significance of cis-abundance using an exact binomial test (Methods), literally every single genome exhibited significantly higher cis fractions than would be expected if the mutations were distributed randomly between the two homologues of a gene (P < 2.55x10 -29 -2.30x10 -10 in EUR, EAS and AMR genomes, 8.83x10 -23 -1.32x10 -07 in AFR genomes). Examining the cis and trans configurations that were constituted by the entirety of AA exchanges, the results were highly similar ( Fig. 1B): individual cis fractions ranged between 54.5 and 64.1% in EUR, EAS and AMR, and between 49.3 and 63.2% in AFR. Cis-abundance was again highly significant in each of the 1,092 genomes, with P < 1.04x10 -67 -2.38x10 -31 in EUR, EAS and AMR genomes, and P < 4.76x10 -60 -3.68x10 -15 in AFR genomes. Finally, also the cis configurations of coding  sSNPs were significantly in excess in each of the 1,092 genomes, with fractions between 57.0 and 66.7% in AMR, EAS and EUR (P < 5.54x10 -94 -7.95x10 -53 ) and between 52.1 and 63.1% in AFR (P < 9.18x10 -69 -7.32 x10 -27 ) (not shown). The seemingly lower variance of cis and trans fractions between individual genomes in the case of AA exchanges and sSNPs was obviously due to the roughly 3-fold higher number of phase-sensitive genes per genome in these cases. Also, each of the 184 experimentally haplotype-resolved PGP genomes exhibited significantly higher cis than trans fractions for each type of coding variants. Specifically, the individual cis fractions of protein-altering mutations varied between 49.4% and 70.8% (P < 2.54×10 -26 -7.99×10 -06 ) (Fig. 1C). Analyzing all AA exchanges, individual cis fractions were between 56.5% and 66.9% (P < 2.46×10 -61 -1.00×10 -38 ) ( Fig.   1D), and the highest in the case of sSNPs, between 57.0 and 69.2% (P < 3.87×10 -93 -9.76×10 -42 ). In sum, these results strongly support the assumption that significant abundance of cis configurations of protein-altering mutations, and of any class of coding variants in general, represents a key characteristic of diploid human genomes. The observation that significant abundance of cis configurations is not restricted to protein-altering mutations suggests a mechanism other than purifying selection underlying the preferential location of mutations on the same chromosomal homologue of a gene. In this context it is important to note that significant cis-abundance was also obtained when analyzing all coding variants together, i.e. protein-altering mutations, other AA exchanges and sSNPs as they co-occur in many genes (cis/trans ratio 58.2% to 41.8%, P < 3.38x10 -89 ).
Supported by the decay of cis fractions in AFR, cis-abundance of coding variants most possibly reflects a yet unrecognized manifestation of linkage disequilibrium (LD) as a common, fundamental feature of genome variation.

Cis-abundance primarily driven by pairs of mutations
The reported cis/trans ratios were obtained from genes with different numbers of variants. Because the probability of variants to occur in a trans configuration increases with the number of variants in a gene, these ratios essentially represent composite values. Therefore we dissected these further, assessing the cis/trans ratios separately for configurations with 2 up to 5 variants, which accounted for 95.7% of all configurations in the case of protein-altering mutations, and similar fractions in the case of AA exchanges and sSNPs, respectively. By far the most frequent configurations of proteinaltering mutations, 66.7%, were found to consist of pairs of mutations, 65.8% of which resided in cis.
The second most frequent configurations, 18.6%, were combinations of 3 mutations, occurring in equal proportions in cis or trans. As expected, the fractions of trans configurations increased to 53.4% in the case of 4 and 60.3% in the case of 5 mutations, accounting, however, for only small fractions of all configurations, 7.3% and 3.1%, respectively (Supplemental Table S2A). Essentially similar results were obtained when dissecting the cis/trans ratios determined from the entirety of AA exchanges and sSNPs; specifically, 57.7% and 59.6%, respectively, of all configurations consisted of pairs of variants, 67.9% and 69.9% of which resided in cis. Finally, analyzing all types of coding variants together, nearly half of all configurations consisted of pairs of variants, 68.7% of which were in cis (Supplemental Table S2B). Dissecting the composite cis/trans ratios separately in AFR, EUR, AMR and EAS showed an excess of pairs of protein-altering mutations also in each ancestry group: these were between 65.5% (AFR) and 67.7% of all configurations, of which 62.4 (AFR)-67.8% resided in cis (Supplemental Table S2A). Dissecting the composite cis/trans ratios in the PGP genomes, the pairs of protein-altering mutations accounted for nearly 65% of all configurations, of which 66.8% were in cis (Supplemental Table S2A). In sum, the dissection of the composite cis/trans ratios shows that the abundance of cis configurations is primarily driven by pairs of mutations that are predominantly in cis.
To estimate the excess of cis configurations we compared observed and theoretically expected cis/trans ratios. The probability P for a configuration with a defined number of n variants to reside in cis is 1/2 n-1 , if the chance for every variant in a gene to occur on either homologue is equal. So for pairs of coding variants, the observed cis/trans ratios were 66:34-70:30 versus expected 50:50; for 13 combinations of 3 variants observed 50:50-54:46 versus expected 25:75, for combinations of 4 variants 45:55-47:53 versus 12.5:87.5, and for 5 variants 39:61-41:59 versus 6.25:93.75. This corresponded to a 1.32-1.4 up to 6.24-6.56-fold enrichment of cis fractions. Then we generated 1,092 virtual, phased genomes, assigning to each variant in a gene a 50:50 chance to exist on either homologue (Methods), and dissected the simulated data set accordingly. The simulated cis/trans ratios being virtually identical for 2 up to 5 variants to the expected ones (as calculated above), we derived the expected composite cis/trans ratios, ~39:61 for protein-altering mutations, ~37:63 for both AA exchanges and sSNPs, respectively, and 33:67 combining all types of coding variants (Supplemental Table S3). Thus, cis/trans ratios observed ~60:40 versus expected below 40:60. These results had provided the basis for the use of an expected probability of 0.4 for a cis configuration to occur, when testing each of the 1,092 genomes for significance of the observed cis fraction. So even where cis ratios are minimally below 50%, which is the case in three of 1,092 genomes, and one of 184 PGP genomes, they are still significantly higher than would be expected by chance. These results underscore the overall tendency of coding variants to reside on the same homologue. Thus, diploid genes have two variable and potentially functionally altered homologues to a far lower extent than expected by chance.

Cis-abundance driven by inter-mutation distance and frequency
In an attempt to explain observed cis-abundance, we considered ancestral admixture as a potential common underlying mechanism. Accordingly, pairs of protein-altering mutations in cis would be closely spaced and common, and pairs of mutations in trans distant and less frequent. So we compared, in a first step, the inter-mutation genome distances between totals of mutation pairs in cis, and trans; these are reported separately for EUR and AFR due to differences in the decay of LD. In effect, pairs of protein-altering mutations in cis were much closer together than pairs in trans, with inter-mutation distances in EUR of 1570 bp (median) versus 5290 bp, and 1830 versus 4771 bp in 14 AFR. The same picture was observed when examining the distances between all pairs of AA exchanges and coding sSNPs, respectively: the variants in cis were much more closely spaced than the variants in trans, and the latter were less distant in AFR than in EUR; the absolute distances were, however, generally larger (Supplemental Table S4). Overall, pairs of variants in cis extended over genome distances up to nearly 3,900 bp (median), and in trans up to nearly 8,000 bp in EUR and ~7,200 bp in AFR (Supplemental Table S4). These results were confirmed by analysis of PGP genomes, with inter-mutation genome distances of 2,584 bp (median) between pairs of protein-altering mutations in cis, and of 5,984 bp between pairs in trans. Examining the distances between all pairs of AA exchanges and sSNPs, respectively, the variants residing in cis spanned genome distances up to 3,562 bp, and the variants in trans distances up to 8,280 bp, largely consistent with the intervals estimated in 1000G (Supplemental Table S4). Where pairs of protein-altering mutations in cis and pairs of coding sSNPs in cis were found to co-exist within a diploid gene, which was the case for roughly 12-15 genes per genome, they were found to reside on the same homologue in over 83% of cases, indicating localization within the same ancestral segment.
In a second step, we examined the relationship of inter-mutation distance with cis/trans ratio. Cis and trans configurations were sorted by inter-mutation distance, binned per 6,000 configurations, and an average inter-mutation distance with its corresponding cis/trans ratio assessed per bin.
Accordingly, the smallest distance in EUR, 11 bp, corresponded to the highest cis/trans ratio, 77:23, which declined to 51:49 at a distance of 54,281 bp and fell marginally below 50% at the largest average inter-mutation distance calculated, 81,099 bp, where a cumulative cis fraction of 67.8% was reached (Supplemental Fig. S1A, B). A similar inverse relationship between average inter-mutation distance and cis/trans ratio was observed in AFR, where an increase of distances from 14 to maximally 57,466 bp correlated with a (more rapid) decrease of cis/trans ratios from 75:25 to 48:52, with a cumulative cis fraction of 62.4% (Supplemental Fig. S1C, D). Analogous analyses performed with the entirety of AA exchanges and coding sSNPs (Supplemental Fig. S1E-H) strongly confirmed this picture. Taken together, significant cis-abundance is primarily due to an excess of pairs of mutations in cis that are closely spaced, while pairs of mutations farther apart are more likely to reside in trans. This suggests that cis-abundance is largely driven by distance.
In a third step, we compared the frequencies of pairs of protein-altering mutations in cis versus trans.
To this end, we determined first the different, unique pairs of mutations that existed in either configuration, for each of the phase-sensitive genes in both EUR and AFR. Then we calculated for each pair the average mutation frequency, averaging the minor allele frequencies (MAFs) of each of the two mutations which were provided by the 1000G database for each ancestry group. Notably, the mutations occurring in pairs were found to exhibit very similar frequencies, and combinations of common mutations with singleton mutations, for instance, were very rarely observed. To begin with, we compared the average mutation frequencies between the totals of mutation pairs in cis versus trans. These (quasi the averages across the average mutation frequencies) were 0.18 and 0.16, respectively, in EUR, and 0.143 and 0.128 in AFR. Then we comparatively evaluated the average mutation frequency spectra. Overall, the frequencies of the mutation pairs in either configuration in both ancestry groups peaked between 0.1 and 0.25 (Supplemental Fig. S2A, B), in striking contrast to the MAF spectrum obtained from the entirety of protein-altering mutations in each of the ancestry groups, where 56% of all mutations in EUR (45% in AFR) had an MAF ≤ 0.01 (Supplemental Fig. S2C).
Then, the average mutation frequency spectrum of pairs in cis in EUR peaked between > 0.2 and ≤ 0.25, and pairs in trans between > 0.15 and ≤ 0.2 (Supplemental Fig. S2A). In AFR, both frequency spectra were highest between > 0.1 and ≤ 0.15 (with pairs in trans exceeding cis), mutation pairs in cis, however, were twice as frequent as pairs in trans between > 0.2 and ≤ 0.25 (Supplemental Fig.   S2B). So pairs of protein-altering mutations in cis overall are more frequent than pairs in trans. In sum, these findings support ancestral admixture as a potential explanation for observed, significant cis-abundance. Accordingly, this phenomenon results primarily from pairs of protein-altering mutations, and coding variants as a whole, that are closely spaced and therefore have been inherited together until present. Thus, they are more common than pairs of mutations in trans which, much farther apart, have been subject to recombination, and also may be due to evolutionary forces other than recombination, such as genetic mutation and positive selection. So pairs of co-occurring protein-altering mutations in cis, which are even closer together than other pairs of coding variants in cis, may represent ancestral signals of potential functional significance, and mark small ancestry segments in the 'mosaic that is the human genome' (Pääbo 2003).
Rather than proceeding with in depth analyses to further elucidate the admixture processes generating cis-abundance of coding variants, we have chosen to prioritize analyses that address the potential biological importance of this phenomenon. In other words, rather than addressing aspects of the history of our species, we have chosen to address primarily the result of this history as it may shape gene and genome function. So we focus in the second part of analyses predominantly on the genes that have mutations predicted to alter protein function in either cis or trans configurations (where phase may have an impact) and underlie the observed cis/trans ratio of ~60:40. Importantly, the internal consistency of described results and the fact that we have obtained nearly identical cis/trans ratios from entirely different wet lab and bioinformatics pipelines earlier (Hoehe et al. 2014) apparently validates the annotation of mutations used here, provided by the 1000 Genomes database or the application of PolyPhen-2 (Adzhubei et al. 2010) and SIFT (Ng and Henikoff 2001) as well as GERP conservation scores (Cooper et al. 2005) in the case of PGP (Methods).

A global set of phase-sensitive genes
First of all, how many, and which genes have two or more protein-altering mutations, which could exist in either cis or trans configurations and constitute observed cis-abundance? Each of the 1,092 genomes had between 393 and 710 such phase-sensitive genes (median 487), equivalent to 2.2-3.9% of all autosomal protein-coding genes (Hg19, RefSeq). In 221-397 (median 297) of these genes, the mutations resided in cis and in 132-342 (median 193) in trans; for corresponding results for each of the four ancestry groups see Supplemental Table S5A, for corresponding numbers from all AA exchanges, which were overall ~2.7-fold higher and affected 5.7-10.3% of all autosomal genes, see Supplemental Table S5B. Taken together, the relatively low level of variation in the fractions of cis and trans configurations observed across the genomes corresponds to a relatively limited range of variation in the numbers of phase-sensitive genes, and their cis and trans forms. These numbers were directly proportional to the numbers of protein-altering mutations in a genome (median 2869) across all ancestry groups. A detailed description of the entire numerical framework that defines the highly specific relationships between mutations and the different categories of mutated genes, as well as the simulation of the proportionality constants through random distribution of mutations onto existing exome structure, is provided in Supplemental Table S6A-D; Supplemental Table S7; see also Supplemental Note. In sum, at the bottom of observed cis-abundance are highly similar numbers of mutations per genome which generate highly similar numbers of phase-sensitive genes, and their cis and trans forms. Thus, to which extent are the genes in each of these categories the same? In other words, is there a common, shared set of phase-sensitive genes? Can we further distinguish within such a set two groups of genes, which have preferentially cis, or trans configurations? In fact, we were able to identify a set of 2,402 genes with protein-altering mutations in either cis or trans configurations, which were shared by all ancestry groups ( Fig. 2; Supplemental Table S8). To this end, we intersected the genes which were phase-sensitive in each of the ancestry groups, 4,000 in EUR, 3,357 in EAS, 4,005 in AMR and 5,217 in AFR, any two of which overlapped by 80-87%. This 'global set of phase-sensitive genes' unveiled a highly significant overrepresentation of manifold gene ontology (GO) terms (Methods) including receptor activity, mainly olfactory, trans-membrane signaling and G-protein coupled receptor (GPCR) activity, the detection of (chemical) stimuli and sensory perception, membrane-and extracellular matrix (ECM)-related components/molecules, cell adhesion, the binding of odorants and antigens, multiple activities involved in the metabolism of Venn diagram showing the set of 2,402 phasesensitive genes (i.e. genes that have ≥ 2 proteinaltering mutations), which is shared by all four ancestry groups AFR, EAS, AMR and EUR (as colorcoded) from the 1000 Genomes database. In addition, the numbers of phase-sensitive genes that are common to any 3 or 2 of these ancestry groups are indicated as well as those that are private to one of these ancestry groups.
substrates and xenobiotics, and MHC proteins (P<6.12x10 -46 -9.56x10 -04 for the top 99 GO groups) (Supplemental Table S9A). These results were complemented by a highly significant enrichment of pathways (Methods) including the transduction of olfactory signals, GPCR signaling and other types of signal transduction, ECM organization/receptor interactions, cell surface interactions, numerous immune-related processes such as antigen processing, Graft-versus-host and autoimmune diseases as well as multiple other diseases, chemical carcinogenesis, numerous biosynthetic and metabolic pathways, e.g. xenobiotics, drug metabolism and transport (P<1.31x10 -52 -9.4x10 -03 for the top 61 pathways; Supplemental Table S9B). 68% of the genes contained in the global set were also found to be phase-sensitive in the 184 experimentally haplotype-resolved genomes. This subset of 1,627 experimentally haplotype-resolved genes was found significantly enriched for similar biological functions. PGP genes shared 78% of the overrepresented GO terms (P<1.30x10 -41 -0.001) and 76% of the pathways (P<6.03x10 -46 -0.01) with the global set (Supplemental Table S9C In this work, we have focused on genes with ≥ 2 mutations to examine the distribution of mutations between the two homologues and global patterns of phase in the diploid human genome. Further analyses unveiled that the global set of phase-sensitive genes is an integral, though substantial part of a larger global set of genes with ≥ 1 protein-altering mutations (Supplemental Table S8) which similarly showed an overrepresentation of described functional categories (Supplemental Table   S10A, B). The disproportionally larger contribution of the genes with ≥ 2 mutations compared to genes with 1 mutation, respectively, to the pathways and GO terms which were significantly enriched, are shown in Supplemental Fig. S4A, B (see Supplemental Note for further detail). Thus, the biological functions under consideration appear to be preferentially controlled by variable genes per se, 'molecular diplotypes' (Hoehe et al. 2014). In contrast, a set of 5,040 genes was identified (Supplemental Table S8), which did not contain any protein-altering mutations at all in the 1,092 genomes and was significantly enriched for numerous essential cellular functions which may not tolerate variability, including pathways involved in cell cycle, gene regulation and epigenetic mechanisms (P<6.15x10 -25 -9.51x10 -11 for the top 50 pathways; P<2.35x10 -24 -2.12x10 -14 for the top 50 GOs) (Supplemental Table S11A, B). Thus, the protein-altering mutations giving rise to both the global set of phase-sensitive and global set of variable genes are not randomly distributed across the exome, as in principle also shown earlier (Hoehe et al. 2014). Thus, evolutionary processes such as balancing selection may have resulted in the maintenance of long term diversity of these genes, preserving their functional flexibility to allow adaptation of the organism to internal and external stimuli and changes of environment. This assumption is supported by significant enrichment of the global set of phase-sensitive genes and, to a lesser extent, the expanded set of variable genes, with genes reported to be under balancing selection (BS) (P = 9.29x10 -07 and P = 4.08x10 -03 , respectively) (Savova et al. 2016). Moreover, both global sets were found significantly enriched for monoallelically expressed (MAE) genes compared to biallelically expressed genes (BAE) (Methods; P = 1.75x10 -11 and 1.99x10 -14 , respectively) (Savova et al. 2016), further corroborating their potential role as major modulators and adaptive agents. A potential evolutionary significance of these gene sets is furthermore indicated by significant enrichment with genes with ancient derived protein-coding polymorphisms or haplotypes predating the human-Neanderthal split (HNS) (Methods; P = 3.09x10 -16 and P = 4.77x10 -12 , respectively) (Savova et al. 2016). The significance of enrichment with genes indicating evolutionary significance (BS, HNS and genes with evidence of human-chimpanzee transspecies polymorphisms (TSP)) is further enhanced when analyzing the set of 1,627 cross-validated phase-sensitive genes which is shared by PGP and the global set of phase-sensitive genes (P = 1.23x10 -09 for BS, P = 6.56 x 10 -2 for TSP, and P = 3.79 x 10 -22 for HNS; see also Supplemental Fig. S5).
Where the genes have ≥ 2 mutations the question arises, how are these mutations distributed between the two homologues of the genes in a population? Can we further distinguish within identified global set of phase-sensitive genes two groups of genes, which have either preferentially cis, or trans configurations of protein-altering mutations? And could these influence the biological functions in question differentially?

Cis-versus trans-abundant genes
To this end, we evaluated first each of the 2,402 phase-sensitive genes across the entirety of 1,092 genomes using a Binomial test (Methods). In effect, we identified a subset of 1,227 genes exhibiting significantly more frequently cis configurations (1.05x10 -63 -0.048), which we defined as 'cis-abundant genes', and 786 genes having significantly more frequently trans configurations (1.78x10 -15 -0.049) defined as 'trans-abundant genes' (Supplemental Table S12A, B). The remainder, 385 genes (16%), had nearly equal proportions of both configurations. In a second approach, we determined first the significantly cis-and trans-abundant genes separately for each ancestry group, which we intersected to derive global sets of cis-and trans-abundant genes. These were identical with the gene sets derived in the first pass, confirming that the specific 'configuration type' of a gene is the same in all population samples. Thus, cis-or trans-abundance could represent a constant characteristic of a gene. In sum, the vast majority (84%) of the autosomal genes with ≥ 2 protein-altering mutations that were contained in the global set can be classified into the two major categories cis-and transabundant genes. These may reflect different mechanisms to exert and regulate gene functions.
So we examined, whether these cis-and trans-abundant genes could be differentially involved in the gene functions (GO terms) and pathways found overrepresented in the global set. In effect, they were found distinctively enriched for a number of pathways: cis-abundant genes for signaling by GPCR and signal transduction, biosynthetic and especially metabolic pathways, e.g. xenobiotics metabolism including cytochrome P450-mediated oxidation and other phase 1-related processes (P<1.81x10 -51 -0.008); trans-abundant genes for numerous immune response-related processes and diseases as well as autoimmune diseases, viral and infectious diseases, cell surface interactions, ECMreceptor interaction, signaling pathways, and drug transport (P<3.26x10 -7 -0.009) (Supplemental Table S13A, B). Thus, the disease-related phenotypes found enriched in the global set appear to be primarily mediated by trans-configurations. Both cis-and trans-abundant genes were significantly over-represented in pathways involving the transduction of olfactory signals, GPCR downstream signaling, and ECM organization (Supplemental Fig. S6A). In sum, over 75% of the pathways found enriched in the global set of phase-sensitive genes could be further distinguished by their preferential involvement of cis-or trans-abundant genes. A similar picture was observed for GO terms: an overrepresentation of significantly cis-abundant genes was for instance observed for GPCR activity and signaling, odorant binding, and activities involved in the metabolism of substrates. Transabundant genes e.g. were enriched for MHC proteins/receptors, antigen binding, ECM structural constituent and organization, and cell adhesion (Supplemental Table S13C, D). Both cis-and transabundant genes were significantly enriched for instance in olfactory and trans-membrane (signaling) receptor activity, the detection of (chemical) stimulus, sensory perception and membrane-related components (Supplemental Fig. S6B). In sum, 57-83% of the GO terms, evaluated separately for their taxonomies, could be further differentiated with regard to their preferential involvement of either gene category. Thus, cis and trans-abundant genes may differentially influence pathways and gene functions.
This classification of autosomal genes has been derived from the global set of phase-sensitive genes, which effectively represents 46-72% of these genes within each ancestry group. To test whether this classification is also valid in a population as a whole, we examined each of these ancestry groups separately. Setting a threshold of 10 configuration counts per gene, 1,173 significantly cis-and 670 trans-abundant genes were obtained in EUR, 966 and 590 in EAS, 981 and 497 in AMR and 1,265 and 817 in AFR, accounting for 78-88% of all autosomal phase-sensitive genes. Essentially similar results were obtained using a threshold of 5% of total genome count. Subsequent analysis of the 184 experimentally haplotype-resolved PGP genomes also validated this classification; correspondingly, 83.5% of the phase-sensitive genes were grouped into 778 significantly cis-and 436 trans-abundant genes. In sum, these results underscore the existence of cis-and trans-abundant genes as major categories of variable autosomal genes. Evidently, the group of cis-abundant genes is always larger than the group of trans-abundant genes, with ratios between 1.55:1 and 2:1. Thus, significant cisabundance is the net result of these two groups. Both cis-and trans-abundant genes were found distributed across the autosomes in varying mixtures, leading to autosomal cis/trans ratios between 53:47 (chr. 10) and 69:31 (chr. 14) (Supplemental Table S14A  Subsequently we examined the specific positions of protein-altering mutations in cis versus trans across the genes. We attempted to identify different distributional patterns of the mutations, not only between, but also within the homologues, which could be functionally relevant. In a first step, we inspected the mutation genomic coordinates in several cross-validated genes in more detail and in fact observed striking differences. Thus, in cis-abundant genes such as for example ZNF546 (Fig.   4A), or ADAM33, PON2, ZNF626 and KRT83, there existed one pair of mutations that dominated the picture. Notably, the two mutations establishing such a 'major configuration' nearly always occurred together, and only rarely, one of the two protein-altering mutations occurred alone, or in combinations with other mutations. In addition to these major configurations, in case, small numbers of other pairs or combinations of mutations in cis or trans were observed (Fig. 4A). A much more mixed picture was observed in trans-abundant genes, as exemplified by KRT3 (Fig. 4B). This was characterized by two or more, apparently less frequent pairs of mutations in trans; in this example, a trans pair existed to a small, but visible extent still in cis. To test whether these case observations     The 'major configuration' of a cis-or trans-abundant gene is defined as the pair of mutations that exhibits the highest number of cis, or trans counts, respectively, relative to the total of cis or trans counts observed for this gene in a population sample. This ratio is defined as the 'major configuration frequency' (MCF) of a gene. The MCFs of defined numbers of genes are binned in 10% intervals. Specifically, they were assessed for 1,227 cis-and 786 trans-abundant genes in 1,092 genomes from the 1000 Genomes (1000G) database, and for the cross-validated sets of 322 cis-and 153 trans-abundant genes which were shared by both 1000G and PGP. (A) The blue bars indicate the numbers of cis-abundant genes (y-axis left) of a total of 1,227 cis-abundant genes, which have a major configuration with a frequency (%) as specified by given bins (x-axis). For example, referring to the highest blue bar on the right, 383 cis-abundant genes have a major configuration with a frequency between > 90 and 100% of total cis count. The black graph represents the cumulative percentage (%) of the number of these genes (yaxis right). (B) Accordingly, MCFs binned for 322 cis-abundant genes from 1000G and (C) for the identical 322 cis-abundant genes assessed in the 184 experimentally phased PGP genomes. The corresponding results for trans-abundant genes (red bars) are presented in (D), (E), and (F).
the entirety of configurations in each of the genes, across the genomes. Then we binned the genes by percentage of their major configuration count. As demonstrated in Fig. 5A, a substantial fraction (31.2%) of the 1,227 cis-abundant genes exhibited one major pair of protein-altering mutations accounting for > 90 up to 100% of all cis configurations, and 42% one major pair accounting for > 80% of all cis configurations. This result was confirmed in the cross-validated genes (Fig. 5B, C). 12-20% of the genes had major pairs of mutations with frequencies of 20% or less; thus, these genes have mostly more frequent combinations of 3 and more mutations, such as BRCA1. A strikingly different picture was observed for trans-abundant genes, characterized by the absence of a major configuration which would be present in sizable fractions ( Fig. 5D-F). In sum, significant cisabundance essentially results from a considerable fraction of cis-abundant genes, which have highly frequent pairs of mutations co-occurring on the same homologue. Thus, we have traced cisabundance back to specific, potentially ancient pairs of protein-altering mutations in cis. Attempting to interpret this finding, we considered epistatic interactions between these pairs of mutations, a potential role as compensatory mutations, or co-evolution. In order to explore whether these major, closely spaced mutation pairs could in fact indicate potential interactions between the mutations, we have mapped them onto protein tertiary structures using the Protein Data Bank (PDB) (Rose et al. 2013). Indeed, for some proteins, for example ESYT2 (Extended Synaptotagmin 2), a membranerelated protein, we found that the corresponding residue pairs existed in close physical distance (~9 Å) (Fig. 6). This could suggest possibility of physical interaction and/or functional interdependence, for instance indicating coevolution (Anishchenko et al. 2017). Rounding up, we have obtained first, very preliminary evidence for potential functional implications of major mutation pairs in cis, the hallmark of cis-abundance. Two neighboring mutations (S584P and S610G) in the protein ESYT2 (Extended Synaptotagmin 2) are shown. Both mutations fall in the C2 domain that targets the protein to the cell membrane.
Mutations are located within a physical distance of ~9 Å, suggesting potential contact between the residue pair. Tertiary structure was taken from the PDB database (ID: 4P42). Mapping was generated with the MuPIT web server (Niknafs et al. 2013). Residue distance was computed with the Chimera software (Pettersen et al. 2004).

d ~9 Å Discussion
This work represents the first large scale analysis of both statistically and experimentally haplotype- It is unlikely that these patterns represent an artifact due to bias in phasing. This statement is supported by (i) the high quality of 1000G statistical haplotype data and their strong validation by analysis of a substantial number of experimentally phased genomes; and (ii) the robustness of the experimental phasing method, ensured by an exceedingly low phasing error rate (Peters et al. 2012).
Thus, additional steps to eliminate potential artifacts as causes of the cis and trans patterns of heterozygous variants, such as independent calculation of LD values from un-phased data, do not appear warranted. While some variation in the absolute numbers of cis and trans configurations of mutations has been observed, possibly due to differences in population structures and size, or annotation and validation procedures, the relative fractions of cis and trans configurations proved to be quite stable. Moreover, it appears unlikely that the cis/trans ratios of mutations predicted to alter the protein were biased by the annotation algorithms used (Hicks et al. 2011;Tennessen et al. 2012;Fu et al. 2013), as entirely different wet lab and bioinformatics pipelines, as well as control analyses of all AA exchanges and sSNPs produced highly similar ratios. Thus, the overall consistency of our data suggests that the key results can be considered robust and not an artifact of the specific algorithms and settings employed, or the parameters used.
This work represents an advance in the field of haplotype analysis in that an established experimental phasing method (Peters et al. 2012) has been applied at the population level to address Project are primarily based on genetic marker concepts, i.e. using LD to infer the position of disease variants, while providing a catalogue of functional variants to help to prioritize candidate disease variants (Abecasis et al. 2012;Auton et al. 2015). In contrast, this work attempts to address the distributional patterns of mutations across genes, between and within the two homologous chromosomes and their potential functional consequences, to help to understand diploid gene and genome function. Cis-abundance of protein-altering mutations and coding variants as a whole, represent yet another face of LD in the human genome, and the relationship between the extended haplotype blocks established by the HapMap or 1000 Genomes Project, and the phased exonic sequences remains to be determined. Essentially, our work shows how the patterns of LD in the human genome (Gabriel et al. 2002;Ardlie et al. 2002) affect the distribution of genetic variants between the two homologous chromosomes of autosomal genes. In this context, it is important to note that due to existing LD a ~50:50 cis/trans ratio of the remaining classes of coding variants could not necessarily be expected in order to support functional significance of cis-abundance of proteinaltering mutations. This issue is related to the challenge of distinguishing the causative variants from those in LD in the context of disease gene identification. Importantly, analogous analyses which we performed solely with AA exchanges other than those predicted to alter protein function, and sSNPs, failed to generate the results obtained with the protein-altering mutations.
Moreover, this work represents a first phase-informed analysis of protein-coding variation in the diploid human exome. Recent exome studies (Li et al. 2010;Tennessen et al. 2012;Fu et al. 2013;Lek et al. 2016;Telenti et al. 2016), in an effort to facilitate identification of potential disease-causing variants, have mainly focused on characterizing the functional spectrum of allelic variation in human genes and the underlying demographic and evolutionary forces that generated this variation. Issues of phase have yet remained unaddressed. Considering a total of 18,121 autosomal genes (RefSeq), phase may be of relevance for 6,284 genes, which have ≥ 2 protein-altering mutations in at least one of 1,092 genomes, while 6,797 genes have at most one mutation and 5,040 autosomal genes not any protein-altering mutations at all. Nearly half of all mutations predicted to functionally alter the protein in a genome (and over 60% of all AA exchanges) were found to exist in either cis or trans configurations and therefore require phase information. An overwhelming majority of all variable autosomal genes with ≥ 2 protein-altering mutations are either cis-or trans-abundant, and so are all genes with AA exchanges and sSNPs. Knowledge of phase is also indispensable in human exomes as there are many genes with mono-allelic or allele-specific expression, especially those modulated by epigenetic phenomena (Gimelbrant et al. 2007;Leung et al. 2015). In this case, the unique distribution of mutations across the two chromosomal homologues affects which mutations will ultimately have functional consequences. Thus, phase is an important link to differentially expressed transcriptomes and proteomes. Future questions to be addressed are which of the two homologues This work has introduced two major categories of variable autosomal genes: cis-and trans-abundant genes. The more frequent cis-abundant genes are characterized by common pairs of closely spaced protein-altering mutations. Thus, these may represent 'evolutionary signals' which trace back to ancient populations. Reasons for their preservation could be epistatic or compensatory interactions between these mutations, maintaining or enhancing the functionality of the protein (Kondrashov et al. 2002;DePristo et al. 2005;Ferrer-Costa et al. 2007; Baresic et al. 2010), co-evolution (Anishchenko et al. 2017), or hitchhiking effects (Slatkin 2008). Evidence for potential physical interaction between such mutation pairs in cis has been obtained in preliminary analyses at the example of ESYT2 (Fig. 6). Once the (available) 3D structures in protein databases are more complete, these seemingly old, co-occurring pairs of protein-altering mutations discovered in this work, may provide valuable information for the study of protein evolution and functionality (DePristo et al. 2005). Trans-abundant genes, on the other hand, apparently result from a mixture of mechanisms, such as the recombination of more distantly spaced mutations (exemplified by mutation pairs, which exist to a small percentage still in cis, while to a larger extent in trans), the occurrence of mutations, or positive selection such as in the case of HLA genes (Bustamante et al. 2005). This latter example referring to the relatively short HLA genes illustrates that configuration status is not significantly influenced by gene length. While trans-abundant genes are on average longer than cis-abundant genes (primary transcript lengths 35,969 bp versus 25,859 bp, P = 3.9x10 -08 ; AA sequence lengths 1,012 versus 875; P = 0.001), corresponding with their much larger inter-mutation genomic distances, the overall correlation between gene-based trans fractions and primary transcript as well as AA length was not significant. Although there is an overall tendency for genes to reside in trans with increasing numbers of mutations, the opposite was true for the highly diverse OR genes. These were largely cis-abundant, their diversity being preserved by positive selection (Bustamante et al. 2005).
Taken together, configuration status on the whole is neither the result of gene length nor the number of mutations. Furthermore, significant overlaps between both cis-and trans-abundant genes and MAE genes were found. First, with regard to the specific (functional) classes they were enriched for and then with regard to the shift of allele frequency distributions in these genes towards those consistent with common variation (i.e. greater allelic age on average (Savova et al. 2016)). Thus, these genes may encode common functional variation in the populations, generating wide-spread cell-to-cell, organismal, and phenotypic diversity. Their significant enrichment with functional classes involved in cell-cell and cell-environment interactions, in all populations examined, supports their general adaptive role (Savova et al. 2016). Moreover, the mutations constituting the common phase configurations might not represent disease mutations, but instead modulate the effect of individual, rare, or disease variants on gene function. To further characterize cis-and trans-abundant genes, that is, genes with either one or two altered homologues, novel approaches to the analysis of sequence-structure-function relationships will be required. These must account for the two different homologues a diploid gene possesses, including new (in vitro) paradigms to both separately and jointly express and characterize the two different gene products. This should also help to elucidate the differential influence of these two gene categories in functional context.
How could we explain the phenomena described? Preliminary results pointed in principle to two major mechanisms. Firstly, cis-abundance, with ~60:40 cis/trans ratios being observed for all types of coding variants, could arise from ancestral admixture as the common underlying mechanism. Further investigations tracing human evolutionary history and population genetic processes will be required to elucidate the apparently ancient origins of cis-abundance and the specific admixture processes generating it. Moreover, the observation that all populations showed approximately the same cis/trans ratios (with some decay of LD in AFR leading to a ~55:45 ratio) suggests that genetic admixture between two ancient populations must have occurred before dispersal of modern humans out of Africa and their population expansion worldwide (Nielsen et al. 2017;McEvoy et al. 2011).
Secondly, a significant overrepresentation of particular functional categories in the global sets of phase-sensitive, and cis-and trans-abundant, genes was observed. With ≥ 2 protein-altering mutations, these genes featured an increased mutational load. As preliminary results indicated, processes of ancient balancing selection may have contributed to their higher genetic diversity to preserve their functional flexibility as an adaptive advantage (Wu and Dunlap 2002;Sellis et al. 2011;Hoehe et al. 2014;Savova et al. 2016). Moreover, the observation that all populations had the same distributional patterns of protein-altering mutations and functional enrichment suggests that these selective processes must have occurred before ancestral admixture. Thus, this conserved, potentially functionally important 'phase-sensitive part' of the diploid human genome may have very ancient origins. This applies particularly also to the common pairs of co-occurring mutations characterizing cis-abundant genes. These could serve as 'evolutionary signals' that could contribute to further elucidate the evolutionary history of the phenomena described. In sum, processes of ancient selection followed by admixture may have shaped the overall picture observed.
This work represents a basis for diploid genomics, or 'diplomics' (Tewhey et al. 2011), a 'dual' view of biological processes. It identifies, and focuses on, those sets of genes, the homologues of which are potentially functionally different (Wu and Dunlap 2002), and divides those further into two categories, cis-and trans-abundant genes (i.e., diploid genes with either one, or two altered homologues). Thus, it sets the stage for a diploid biology which inherently is allelically biased at all levels: chromatin organization, epigenomes, transcriptomes including transcriptional regulation, and proteomes (Dixon et al. 2015;Leung et al. 2015). Diploid biology will need to be described and understood with reference to the two homologues of the genes and regulatory sequences an individual possesses. In this context it should be pointed out what a challenge it is to currently describe the diploid nature of human genomes in words and terms that have been shaped by working with un-phased, i.e. 'mixed diploid' sequences leading to the perception and interpretation of a 'one genome world'. Towards diploid genomics, major questions to be addressed in the future are, for example, whether, and how, biology could change with cis/trans ratios, or how phenotype could change with configuration status, and whether cis-abundance could represent a general phenomenon in all diploid species. Importantly, a large number of technical replicate samples were generated to measure phasing error rates. As demonstrated previously (Peters et al. 2012), these error rates were exceedingly low (Mao et al. 2016) with ~86% of overlapping blocks between replicate samples completely error-free. Data from these samples was projected onto a principle component analysis using four populations from the HapMap project. This confirmed that the self-reported ethnicities from each participant matched their genetic profile. Importantly, for analyses in this study, a contig filter was applied to ensure that phase configurations were determined only for those protein-altering mutations and coding variants that were contained within the same contig.

Annotation of mutations, assessment of cis and trans configurations, evaluation of cis/trans ratios
RefSeq genes were downloaded from UCSC  Hoehe et al. 2014). For the analysis of PGP data, we applied PolyPhen-2 and SIFT in combination with GERP (as described above) to the PGP output files generated from each of the 184 experimentally phased genomes and prepared the intermediate output files accordingly.
To assess the concrete phase configurations of all 'phase-sensitive' autosomal genes with ≥ 2 mutations in each of the genomes, we applied and automated the following approach: Examine column 1 representing 'Haplotype 1' by moving 5' to 3' from cell to cell, each containing allele 1 or 0 assigned to a genomic coordinate and gene ID. Remove all genes that have only one protein-altering mutation, i.e. only one cell assigned to a gene ID, to ensure that only those mutations are included that require phasing. (Upon removal of genes with one mutation, the number of different gene IDs is equivalent to the number of phase-sensitive genes in the individual genome under investigation.) Store the series of alleles across all cells (within column 1) assigned to the same gene ID as units and subject these to the assessment of phase configurations: where all stored alleles in column 1 are exclusively 1s or 0s, a cis configuration is scored, otherwise a trans configuration (see also Hoehe et al. 2014). Thus, for each genome, a result file was generated, which contained the gene IDs with an assignment of cis or trans.
This allowed immediate calculation of the cis fraction (%) of an individual genome as the number of genes with cis configurations divided by total number of genes with ≥ 2 mutations, i.e. total configuration count (equivalent to 100%), and of the trans fraction (%) per genome as 100% -cis (%).
To determine the cis/trans ratio for totals of 1,092 or 184 genomes, or any population sample, the median values of the cis, and the trans fractions were calculated across all genomes.
To evaluate the significance of a given cis/trans ratio in an individual genome, we derived the composite probability of a cis, or trans configuration across all genes. We can model the probability of an observed cis, or trans configuration in a gene with i mutations with a Bernoulli experiment ( = 1) where = 1 denotes a cis configuration and = 0 a trans configuration. Thus, we have ( = 1) = 1 2 −1 and ( = 0) = 1 − 1 2 −1 . Among the number of genes with ≥ 2 mutations that have either cis or trans configurations, let be the relative frequency of genes with exactly i mutations. Thus, we have ∑ ≥2 = 1. The probability of observing a cis configuration among all phase-sensitive genes in a genome is then given by the weighted sum of the above defined Bernoulli probabilities: ( = 1) = ∑ ≥2 ( = 1). Thus, inserting the relative observed frequencies, , yielded an expected probability of ~0.4 for a cis configuration to occur. The significance of the observed cis/trans ratio for a given genome was then computed with an exact Binomial test with P = 0.4. To assess the significance values for a cis/trans ratio which was calculated in a population sample, such as the 1,092 or 184 genomes, we derived the median values for both cis and trans configurations across all genomes, quasi a 'median genome'. This was then treated as an individual genome as described above, in order to calculate a significance value for a given population sample.
Thus, the significance values estimated for global cis/trans ratios most likely represent an underestimation.

Simulation of phased genomes, derivation of expected cis/trans ratios
To verify the theoretical assumptions on the composite probability of a cis or trans configuration, simulations of phase were performed assuming that the mutations are distributed randomly between the two homologues of a gene. Accordingly, a virtual set of 1,092 phased genomes was generated as follows: for each virtual genome, random numbers of mutations were drawn in the range observed in the 1,092 genomes data set (~2,500-3,500). The mutations were sampled from the total of ~300,000 protein-altering mutations annotated in this data set. Phase was simulated assigning to every single mutation in a gene a 50:50 chance to exist on either homologue 1 or 2.
Practically this was achieved by randomly drawing with each mutation a phase, i.e. 'homologue 1' or 'homologue 2' attached, from the 1000G database. Accordingly, a random distribution of all nsSNPs between the two homologues was simulated, drawing randomly between ~5,500 and ~7,500 nsSNPs with either homologue 1 or 2 attached from the entire pool of ~1.5 Mio nsSNPs annotated in the 1,092 'real' genomes, thus generating a second virtual set of 1,092 phased genomes. To test the validity of our approach to simulate phase, we assessed the cis/trans ratios separately for 2 up to 5 variants in both virtual data sets, and compared these ratios to the probabilities P for these numbers of variants to occur in cis under conditions of random distribution, which is 1/2 n-1 , with n the number of variants. Comparative evaluation showed that the cis/trans ratios which were simulated for defined numbers of variants were essentially identical to those expected. Thus, the simulated data were considered valid and the (composite) expected cis/trans ratios across all genomes in both virtual data sets were derived. The expected cis/trans ratios provided the basis for the estimation of the significance values of the observed cis/trans ratios.
The two virtual sets of 1,092 phased genomes also provided the basis to simulate the highly proportional relationships between the number of mutations per genome and the numbers of genes with 1 mutation, ≥ 2 mutations, cis and trans configurations (as mentioned in the chapter on 'a global set of phase-sensitive genes'; see also Supplemental Table S7) as the result of a random distribution of mutations onto existing exome structure.

Distinction of cis-and trans-abundant genes
To identify cis or trans-abundant genes, that is, genes with ≥ 2 mutations exhibiting either configuration in significant excess, we examined the ratio of cis to trans configurations for each single gene (the 'gene-based' cis/trans ratio) across all genomes in a defined population sample. Significant abundance of either configuration was evaluated with a Binomial test: Given a phase-sensitive gene, let X be a random variable that describes the number of k (out of n) genomes for which a cisconfiguration consisting of two or more mutations has been found (n = 1,092 or any other sample size specified), we computed the corresponding P-value of the Binomial test with null hypothesis that cis and trans configurations were equally likely: . In contrast to the calculations above we used the more stringent assumption of P = 0.5 for a cis configuration as null hypothesis in order to identify cis-abundance for genes in the majority of genomes. Genes with P-value ≤ 0.05 were defined as cis-abundant. Likewise, genes with P-value ≤ 0.05 when counting the trans configurations were defined as trans-abundant.

Over-representation analysis
In order to assess significance of over-representation of gene lists in pre-annotated gene sets (for example pathways, gene ontology (GO) terms, pre-defined gene lists, etc.) we used the hypergeometric distribution. For each annotation set, the P-value is calculated as: , where x is the number of entities in the respective gene list that overlap with the entities in the annotation set, n is the total number of entities in the annotation set, m is the total number of entities in the gene list and N is the total number of genes (background). Since many annotation sets were tested, we routinely corrected for multiple hypothesis testing using the False Discovery Rate procedure within each type of annotation set (Benjamini and Hochberg 1995). For functional testing, we used the ConsensusPathDB tool (version 32) which holds 5,068 pre-defined pathway gene sets along with the latest GO terms (Herwig et al. 2016). Pre-defined gene lists from literature included genes that were found monoallelically (4,227 genes) and biallelically (6,006) expressed across multiple cell lines, 226 genes reported to evolve under balancing selection (BS), 104 genes with ancient derived protein-coding polymorphisms or haplotypes predating the human-Neanderthal split (HNS) and 60 genes with any evidence of human-chimpanzee trans-species polymorphisms or haplotypes (TSPs), as described in Savova et al. (2016). As input gene lists we have used the global set of 2,402 phase-sensitive genes as well as the global set of 7,524 genes with ≥ 1 protein-altering mutations, and, additionally, the 5,040 genes without any mutations. Furthermore, we investigated over-representation with respect to the sets of 1,227 cis-and 786 trans-abundant genes. These gene lists were computed from the 2,402 phase-sensitive genes as described above.

Data Access
Read and mapping data for all genomes reported here are available at the database of Genotypes and Phenotypes (dbGaP) under study accession number phs000905.v1.p1. In addition, the full data package minus reads and mappings are accessible through GigaDB as part of Mao et al. (2016).