Genomic structure and evolution of multigene families: "flowers" on the human genome

Finding relationships among biological entities

Confusion over the concepts of “relationships” and “similarities” lies at the heart of many battles over the direction and intent of research projects. Here is a short story that demonstrates the difference between the two concepts: You look up at the clouds, and you begin to see the shape of a lion. The cloud has a tail, like a lion’s tale, and a fluffy head, like a lion’s mane. With a little imagination the mouth of the lion seems to roar down from the sky. You have succeeded in finding similarities between the cloud and a lion. If you look at a cloud and you imagine a tea kettle producing a head of steam and you recognize that the physical forces that create a cloud and the physical forces that produced steam from a heated kettle are the same, then you have found a relationship. Most popular classification algorithms operate by grouping together data objects that have similar properties or values. In so doing, they may miss finding the true relationships among objects. Traditionally, relationships among data objects are discovered by an intellectual process. In this chapter, we will discuss the scientific gains that come when we classify biological entities by relationships, not by their similarities.

Novel human sex-typing strategies based on the autism candidate gene NLGN4X and its male-specific gametologue NLGN4Y

Background

Since the early days of PCR techniques, sex identification, “sex-typing,” of genomic DNA samples has been a fundamental part of human forensic analysis but also in animal genetics aiming at strategic livestock breeding. Most analyses are employing the AMELX/AMELY gene loci on the X and Y chromosomes present in most mammals. We hypothesize that sex-typing in humans is also possible based on the genes NLGN4X and NLGN4Y, which represent X and Y chromosome-specific copies of a common ancestral neuroligin-4 orthologue.

Methods

Genomic DNA was isolated from human blood and buccal cell samples (total n = 111) and submitted to two different strategies: (a) a traditional two-primer PCR approach detecting an insertion/deletion (indel) polymorphism immediately upstream of the translational start on exon 1 and (b) detection of a single nucleotide polymorphism, SNP, on the translational stop carrying exon 7. The SNP detection was based on a quantitative PCR approach (rhAMP genotyping) employing DNA/RNA hybrid oligonucleotides that were blocked and which could only be activated upon perfect annealing to the target DNA sequence.

Results

All indel PCR-tested human DNA samples showed two bands for males representing X- and Y-specific copies of NLGN4 and a single band for female samples, i.e., homozygosity of NLGN4X and absence of NLGN4Y, in accordance with the self-reported sex of the donors. These results were in perfect agreement with the results of the rhAMP-based SNP-detection method: all males were consequently positive for both alleles, representing either SNP variant, and females were interpreted as homozygous regarding the SNP variant found in NLGN4X. Both methods have shown reliable and consistent results that enabled us to infer the sex of donor DNA samples across different ethnicities.

Conclusions

These results indicate that the detection of human NLGN4X/Y is a suitable alternative to previously reported methods employing gene loci such as AMELX/Y. Furthermore, this is the first report applying successfully the rhAMP-genotyping strategy as a means for SNP-based sex-typing, which consequently will be applicable to other gene loci or different species as well.

Global patterns of large copy number variations in the human genome reveal complexity in chromosome organization

Global patterns of copy number variations (CNVs) in chromosomes are required to understand the dynamics of genome organization and complexity. For this study, analysis was performed using the Affymetrix Genome-Wide Human SNP Array 6.0 chip and CytoScan High-Density arrays. We identified a total of 44 109 CNVs from 1715 genomes with a mean of 25 CNVs in an individual, which established the first drafts of population-specific CNV maps providing a rationale for prioritizing chromosomal regions. About 19 905 ancient CNVs were identified across all chromosomes and populations at varying frequencies. CNV count, and sometimes CNV size, contributed to the bulk CNV size of the chromosome. Population specific lengthening and shortening of chromosomal length was observed. Sex bias for CNV presence was largely dependent on ethnicity. Lower CNV inheritance rate was observed for India, compared to YRI and CEU. A total of 33 candidate CNV hotspots from 5382 copy number (CN) variable region (CNVR) clusters were identified. Population specific CNV distribution patterns in p and q arms disturbed the assumption that CNV counts in the p arm are less common compared to long arms, and the CNV occurrence and distribution in chromosomes is length independent. This study unraveled the force of independent evolutionary dynamics on genome organization and complexity across chromosomes and populations.

Impact of copy number variations burden on coding genome in humans using integrated high resolution arrays

Copy number variations (CNVs) alter the transcriptional and translational levels of genes by disrupting the coding structure and this burden of CNVs seems to be a significant contributor to phenotypic variations. Therefore it was necessary to assess the complexities of CNV burden on the coding genome. A total of 1715 individuals from 12 populations were used for CNV analysis in the present investigation. Analysis was performed using Affymetrix Genome-Wide Human SNP Array 6·0 chip and CytoScan High-Density arrays. CNVs were more frequently observed in the coding region than in the non-coding region. CNVs were observed vastly more frequently in the coding region than the non-coding region. CNVs were found to be enriched in the regions containing functional genes (83-96%) compared with the regions containing pseudogenes (4-17%). CNVs across the genome of an individual showed multiple hits across many genes, whose proteins interact physically and function under the same pathway. We identified varying numbers of proteins and degrees of interactions within protein complexes of single individual genomes. This study represents the first draft of a population-specific CNV genes map as well as a cross-populational map. The complex relationship of CNVs on genes and their physically interacting partners unravels many complexities involved in phenotype expression. This study identifies four mechanisms contributing to the complexities caused by the presence of multiple CNVs across many genes in the coding part of the genome.

Unravelling the complexity of human olfactory receptor repertoire by copy number analysis across population using high resolution arrays

Olfactory receptors (OR), responsible for detection of odor molecules, belong to the largest family of genes and are highly polymorphic in nature having distinct polymorphisms associated with specific regions around the globe. Since there are no reports on the presence of copy number variations in OR repertoire of Indian population, the present investigation in 43 Indians along with 270 HapMap and 31 Tibetan samples was undertaken to study genome variability and evolution. Analysis was performed using Affymetrix Genome-Wide Human SNP Array 6.0 chip, Affymterix CytoScan^® High-Density array, HD-CNV, and MAFFT program. We observed a total of 1527 OR genes in 503 CNV events from 81.3% of the study group, which includes 67.6% duplications and 32.4% deletions encompassing more of genes than pseudogenes. We report human genotypic variation in functional OR repertoire size across populations and it was found that the combinatorial effect of both “orthologous obtained from closely related species” and “paralogous derived sequences” provide the complexity to the continuously occurring OR CNVs.