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Abstract Background With over 1.3 billion people, India is estimated to contain three times more genetic diversity than does Europe. Next-generation sequencing technologies have facilitated the understanding of diversity by enabling whole genome sequencing at greater speed and lower cost. While genomes from people of European and Asian descent have been sequenced, only recently has a single male genome from the Indian subcontinent been published at sufficient depth and coverage. In this study we have sequenced and analyzed the genome of a South Asian Indian female (SAIF) from the Indian state of Kerala. Results We identified over 3.4 million SNPs in this genome including over 89,873 private variations. Comparison of the SAIF genome with several published personal genomes revealed that this individual shared ~50% of the SNPs with each of these genomes. Analysis of the SAIF mitochondrial genome showed that it was closely related to the U1 haplogroup which has been previously observed in Kerala. We assessed the SAIF genome for SNPs with health and disease consequences and found that the individual was at a higher risk for multiple sclerosis and a few other diseases. In analyzing SNPs that modulate drug response, we found a variation that predicts a favorable response to metformin, a drug used to treat diabetes. SNPs predictive of adverse reaction to warfarin indicated that the SAIF individual is not at risk for bleeding if treated with typical doses of warfarin. In addition, we report the presence of several additional SNPs of medical relevance. Conclusions This is the first study to report the complete whole genome sequence of a female from the state of Kerala in India. The availability of this complete genome and variants will further aid studies aimed at understanding genetic diversity, identifying clinically relevant changes and assessing disease burden in the Indian population.

Abstract Background Gene clusters containing multiple similar genomic regions in close proximity are of great interest for biomedical studies because of their associations with inherited diseases. However, such regions are difficult to analyze due to their structural complexity and their complicated evolutionary histories, reflecting a variety of large-scale mutational events. In particular, conversion events can mislead inferences about the relationships among these regions, as traced by traditional methods such as construction of phylogenetic trees or multi-species alignments. Results To correct the distorted information generated by such methods, we have developed an automated pipeline called CHAP (Cluster History Analysis Package) for detecting conversion events. We used this pipeline to analyze the conversion events that affected two well-studied gene clusters (α-globin and β-globin) and three gene clusters for which comparative sequence data were generated from seven primate species: CCL (chemokine ligand), IFN (interferon), and CYP2abf (part of cytochrome P450 family 2). CHAP is freely available at http://www.bx.psu.edu/miller_lab. Conclusions These studies reveal the value of characterizing conversion events in the context of studying gene clusters in complex genomes.

Abstract Background The most common application for the next-generation sequencing technologies is resequencing, where short reads from the genome of an individual are aligned to a reference genome sequence for the same species. These mappings can then be used to identify genetic differences among individuals in a population, and perhaps ultimately to explain phenotypic variation. Many algorithms capable of aligning short reads to the reference, and determining differences between them have been reported. Much less has been reported on how to use these technologies to determine genetic differences among individuals of a species for which a reference sequence is not available, which drastically limits the number of species that can easily benefit from these new technologies. Results We describe a computational pipeline, called DIAL (De novo Identification of Alleles), for identifying single-base substitutions between two closely related genomes without the help of a reference genome. The method works even when the depth of coverage is insufficient for de novo assembly, and it can be extended to determine small insertions/deletions. We evaluate the software's effectiveness using published Roche/454 sequence data from the genome of Dr. James Watson (to detect heterozygous positions) and recent Illumina data from orangutan, in each case comparing our results to those from computational analysis that uses a reference genome assembly. We also illustrate the use of DIAL to identify nucleotide differences among transcriptome sequences. Conclusions DIAL can be used for identification of nucleotide differences in species for which no reference sequence is available. Our main motivation is to use this tool to survey the genetic diversity of endangered species as the identified sequence differences can be used to design genotyping arrays to assist in the species' management. The DIAL source code is freely available at http://www.bx.psu.edu/miller_lab/.

Abstract Background High-throughput custom designed genotyping arrays are a valuable resource for biologically focused research studies and increasingly for validation of variation predicted by next-generation sequencing (NGS) technologies. We investigate the Illumina GoldenGate chemistry using custom designed VeraCode and sentrix array matrix (SAM) assays for each of these applications, respectively. We highlight applications for interpretation of Illumina generated genotype cluster plots to maximise data inclusion and reduce genotyping errors. Findings We illustrate the dramatic effect of outliers in genotype calling and data interpretation, as well as suggest simple means to avoid genotyping errors. Furthermore we present this platform as a successful method for two-cluster rare or non-autosomal variant calling. The success of high-throughput technologies to accurately call rare variants will become an essential feature for future association studies. Finally, we highlight additional advantages of the Illumina GoldenGate chemistry in generating unusually segregated cluster plots that identify potential NGS generated sequencing error resulting from minimal coverage. Conclusions We demonstrate the importance of visually inspecting genotype cluster plots generated by the Illumina software and issue warnings regarding commonly accepted quality control parameters. In addition to suggesting applications to minimise data exclusion, we propose that the Illumina cluster plots may be helpful in identifying potential in-put sequence errors, particularly important for studies to validate NGS generated variation.

Abstract Background The scientific literature contains many examples where DNA sequence analyses have been used to provide definitive answers to phylogenetic problems that traditional (non-DNA based) approaches alone have failed to resolve. One notable example concerns the rhinoceroses, a group for which several contradictory phylogenies were proposed on the basis of morphology, then apparently resolved using mitochondrial DNA fragments. Results In this study we report the first complete mitochondrial genome sequences of the extinct ice-age woolly rhinoceros (Coelodonta antiquitatis), and the threatened Javan (Rhinoceros sondaicus), Sumatran (Dicerorhinus sumatrensis), and black (Diceros bicornis) rhinoceroses. In combination with the previously published mitochondrial genomes of the white (Ceratotherium simum) and Indian (Rhinoceros unicornis) rhinoceroses, this data set putatively enables reconstruction of the rhinoceros phylogeny. While the six species cluster into three strongly supported sister-pairings: (i) The black/white, (ii) the woolly/Sumatran, and (iii) the Javan/Indian, resolution of the higher-level relationships has no statistical support. The phylogenetic signal from individual genes is highly diffuse, with mixed topological support from different genes. Furthermore, the choice of outgroup (horse vs tapir) has considerable effect on reconstruction of the phylogeny. The lack of resolution is suggestive of a hard polytomy at the base of crown-group Rhinocerotidae, and this is supported by an investigation of the relative branch lengths. Conclusion Satisfactory resolution of the rhinoceros phylogeny may not be achievable without additional analyses of substantial amounts of nuclear DNA. This study provides a compelling demonstration that, in spite of substantial sequence length, there are significant limitations with single-locus phylogenetics. We expect further examples of this to appear as next-generation, large-scale sequencing of complete mitochondrial genomes becomes commonplace in evolutionary studies. "The human factor in classification is nowhere more evident than in dealing with this superfamily (Rhinocerotoidea)." G. G. Simpson (1945)