Farnesoid X receptor activation by the novel agonist TC-100 (3α, 7α, 11ß-Trihydroxy-6α-ethyl-5ß-cholan-24-oic Acid) preserves the intestinal barrier integrity and promotes intestinal microbial reshaping in a mouse model of obstructed bile acid flow.

The intestinal tract hosts the gut microbiota (GM), actively shaping health. Bile acids(BAs) are both digestive and signaling molecules acting as hormones via the activation of farnesoid X receptor (FXR). Obstruction of bile flow initiates a cascade of pathological events ultimately leading to intestinal mucosal injury. Administration of BAs in models of obstructed bile flow counteracts these detrimental effects. Objective of this study was to investigate the effects of the novel FXR agonist 3α, 7α, 11ß-Trihydroxy-6α-ethyl-5ß-cholan-24-oic Acid (TC-100) on intestinal mucosa integrity and cecal microbiome composition after surgical bile duct ligation (BDL), a rodent model causing bile flow obstruction. Pharmacological FXR activation was accomplished by daily oral gavage with TC-100 for 5 days. 2 days after treatment initiation, BDL was performed. BAs measurement was carried out and the 16S rDNA (V5-V6 hyper-variable regions) extracted from the cecal content was sequenced. TC-100 activates Fxr in the gut-liver axis and this translated into a significant reduction of serum and bile BA pool size with a shift to a more hydrophilic composition, while signs of intestinal mucosal damage were prevented. Firmicutes:Bacteroidota ratio progressively increased from Sham Operated (SO) mice to TC-100-treated mice. LEfSe analysis showed that Verrucomicrobia, and particularly Akkermansia muciniphila (Amuc) increasingly recognized for improving gut homeostasis and immune functions, were strongly associated to TC-100-treated mice. Intriguingly, Amuc abundance was also negatively associated to cholic acid levels. Collectively, these data indicate that intestinal FXR activation by TC-100 prevents early signs of intestinal mucosal damage by modulating BA homeostasis and GM composition.

Gene electrotransfer of IL-2 and IL-12 plasmids effectively eradicated murine B16.F10 melanoma.

Gene therapy has become an important approach for treating cancer, and electroporation represents a technology for introducing therapeutic genes into a cell. An example of cancer gene therapy relying on gene electrotransfer is the use of immunomodulatory cytokines, such as interleukin 2 (IL-2) and 12 (IL-12), which directly stimulate immune cells at the tumour site. The aim of our study was to determine the effects of gene electrotransfer with two plasmids encoding IL-2 and IL-12 in vitro and in vivo. Two different pulse protocols, known as EP1 (600 V/cm, 5 ms, 1 Hz, 8 pulses) and EP2 (1300 V/cm, 100 µs, 1 Hz, 8 pulses), were assessed in vitro for application in subsequent in vivo experiments. In the in vivo experiment, gene electrotransfer of pIL-2 and pIL-12 using the EP1 protocol was performed in B16.F10 murine melanoma. Combined treatment of tumours using pIL2 and pIL12 induced significant tumour growth delay and 71% complete tumour regression. Furthermore, in tumours coexpressing IL-2 and IL-12, increased accumulation of dendritic cells and M1 macrophages was obtained along with the activation of proinflammatory signals, resulting in CD4 + and CD8 + T-lymphocyte recruitment and immune memory development in the mice. In conclusion, we demonstrated high antitumour efficacy of combined IL-2 and IL-12 gene electrotransfer protocols in low-immunogenicity murine B16.F10 melanoma.

IS26 mediated antimicrobial resistance gene shuffling from the chromosome to a mosaic conjugative FII plasmid.

In the present study we report the identification of a sul3-associated class 1 integron containing the dfrA12-orfF-aadA2-cmlA1-aadA1-qacH array embedded in a Tn21-derived element that is part of a conjugative FII plasmid named pST1007-1A. The plasmid was identified in the Salmonella Typhimurium strain ST1007, a member of a clinically relevant clonal MDR lineage diffuse in Italy. ST1007 exhibited resistance to ampicillin, chloramphenicol, streptomycin, sulphamethoxazole, tetracycline and trimethoprim encoded by blaTEM-1, cmlA1, (aadA1, aadA2, strAB), (sul2, sul3), tet(B) and dfrA12 genes, respectively. Apart from pST1007-1A, ST1007 also harbours two chromosome-integrated resistance units RU1 (blaTEM-1-sul2-strAB) and RU2 (tet(B)), flanked by IS26 elements. RU1 and RU2 were able to move as translocatable units, respectively TU1 and TU2, and integrate via IS26 mediated recombination into pST1007-1A. A family of conjugative plasmids, harbouring different sets of antimicrobial resistance genes (ARG) was then generated: pST1007-1B (dfrA12-aadA2-cmlA1-aadA1-sul3- tet(B)), pST1007-1C (dfrA12-aadA2-cmlA1-aadA1-sul3-blaTEM-1-sul2-strAB), pST1007-1D (blaTEM-1-sul2-strAB), pST1007-1E (tet(B)) and pST1007-1F (dfrA12-aadA2-cmlA1-aadA1-sul3- tet(B) -blaTEM-1-sul2-strAB). pST1007-1A is also a mosaic plasmid containing two distinct DNA fragments acquired from I1 plasmids through recombination within the repA4, rfsF and repeat-3 sites. This study further highlights the role played by IS26 in intracellular ARGs shuffling. Moreover, attention has been focused on recombination hot spots that might play a key role in generating mosaic plasmids.

Pilot study on circulating miRNA signature in children with obesity born small for gestational age and appropriate for gestational age.

BACKGROUND: Children born small for gestational age (SGA) are at increased risk of metabolic dysfunction. Dysregulation of specific microRNAs (miRNAs) contributes to aberrant gene expression patterns underlying metabolic dysfunction. OBJECTIVE: We aimed to determine and compare circulating miRNA (c-miRNA) profile of SGA and appropriate for gestational age (AGA) children with obesity and with normal weight, in order to identify biomarkers for early detection of increased risk of developing metabolic dysfunction in SGA and AGA children with obesity. METHODS: Small non-coding RNAs from serum of 15 SGA children with obesity (OB-SGA), 10 SGA children with normal weight (NW-SGA), 17 AGA children with obesity (OB-AGA) and 12 AGA children with normal weight (NW-AGA) (mean age 11.2 ± 2.6) have been extracted and sequenced in order to detect and quantify miRNA expression profiles. RESULTS: RNA-seq analyses showed 28 miRNAs dysregulated in OB-SGA vs. NW-SGA and 19 miRNAs dysregulated in OB-AGA vs. NW-AGA. Among these, miR-92a-3p, miR-122-5p, miR-423-5p, miR-484, miR-486-3p and miR-532-5p were up regulated, and miR-181b-5p was down regulated in both OB-SGA and OB-AGA compared with normal weight counterparts. Pathway analysis and miRNA target prediction suggested that these miRNAs were particularly involved in insulin signalling, glucose transport, insulin resistance, cholesterol and lipid metabolism. CONCLUSION: We identified a specific profile of c-miRNAs in SGA and AGA children with obesity compared with SGA and AGA children with normal weight. These c-miRNAs could represent specific biomarkers for early detection of increased risk of developing metabolic dysfunction in SGA and AGA children with obesity.

Transcriptomic analysis of nickel exposure in Sphingobium sp. ba1 cells using RNA-seq.

Nickel acts as cofactor for a number of enzymes of many bacteria species. Its homeostasis is ensured by proteins working as ion efflux or accumulation systems. These mechanisms are also generally adopted to counteract life-threatening high extra-cellular Ni2+ concentrations. Little is known regarding nickel tolerance in the genus Sphingobium. We studied the response of the novel Sphingobium sp. ba1 strain, able to adapt to high Ni2+ concentrations. Differential gene expression in cells cultured in 10 mM Ni2+, investigated by RNA-seq analysis, identified 118 differentially expressed genes. Among the 90 up-regulated genes, a cluster including genes coding for nickel and other metal ion efflux systems (similar to either cnrCBA, nccCBA or cznABC) and for a NreB-like permease was found. Comparative analyses among thirty genomes of Sphingobium species show that this cluster is conserved only in two cases, while in the other genomes it is partially present or even absent. The differential expression of genes encoding proteins which could also work as Ni2+-accumulators (HupE/UreJ-like protein, NreA and components of TonB-associated transport and copper-homeostasis systems) was also detected. The identification of Sphingobium sp. ba1 strain adaptive mechanisms to nickel ions, can foster its possible use for biodegradation of poly-aromatic compounds in metal-rich environments.

RNA editing signature during myeloid leukemia cell differentiation.

Adenosine deaminases acting on RNA (ADARs) are key proteins for hematopoietic stem cell self-renewal and for survival of differentiating progenitor cells. However, their specific role in myeloid cell maturation has been poorly investigated. Here we show that ADAR1 is present at basal level in the primary myeloid leukemia cells obtained from patients at diagnosis as well as in myeloid U-937 and THP1 cell lines and its expression correlates with the editing levels. Upon phorbol-myristate acetate or Vitamin D3/granulocyte macrophage colony-stimulating factor (GM-CSF)-driven differentiation, both ADAR1 and ADAR2 enzymes are upregulated, with a concomitant global increase of A-to-I RNA editing. ADAR1 silencing caused an editing decrease at specific ADAR1 target genes, without, however, interfering with cell differentiation or with ADAR2 activity. Remarkably, ADAR2 is absent in the undifferentiated cell stage, due to its elimination through the ubiquitin-proteasome pathway, being strongly upregulated at the end of the differentiation process. Of note, peripheral blood monocytes display editing events at the selected targets similar to those found in differentiated cell lines. Taken together, the data indicate that ADAR enzymes play important and distinct roles in myeloid cells.

MetaShot: an accurate workflow for taxon classification of host-associated microbiome from shotgun metagenomic data.

SUMMARY: Shotgun metagenomics by high-throughput sequencing may allow deep and accurate characterization of host-associated total microbiomes, including bacteria, viruses, protists and fungi. However, the analysis of such sequencing data is still extremely challenging in terms of both overall accuracy and computational efficiency, and current methodologies show substantial variability in misclassification rate and resolution at lower taxonomic ranks or are limited to specific life domains (e.g. only bacteria). We present here MetaShot, a workflow for assessing the total microbiome composition from host-associated shotgun sequence data, and show its overall optimal accuracy performance by analyzing both simulated and real datasets. AVAILABILITY AND IMPLEMENTATION: https://github.com/bfosso/MetaShot. CONTACT: graziano.pesole@uniba.it. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A novel group of IncQ1 plasmids conferring multidrug resistance.

The IncQ is a group of non-conjugative but mobilisable plasmids that are found and stably maintained in a wide range of bacteria contributing to the spread of antimicrobial resistance genes and to the insurgence of multidrug resistant bacteria. Here we report the identification, in clinical Salmonella Typhimurium strains, of an IncQ1 plasmid (pNUC) which confers resistance to sulfamethoxazole, streptomycin and tetracycline through the presence of sul2, strAB and tetA genes, respectively. pNUC was detected in five multidrug resistant S. Typhimurium strains collected in Southern Italy from various hospitals and years of isolation. Bioinformatics analyses highlighted the presence of pNUC-like plasmids in pathogenic bacteria of various Enterobacteriaceae genera or species. Taken as a whole, these plasmids constitute a novel group of IncQ1 plasmids that might have originated through recombination events between a tetR-tetA gene cluster (possibly derived from a Tn1721) and a recipient IncQ1 plasmid related to RSF1010. Our findings raise concerns regarding the possible contribution of the newly identified group of IncQ1 plasmids to the spread of tetracycline resistance.

Diversity and temporal patterns of planktonic protist assemblages at a Mediterranean Long Term Ecological Research site.

We tracked temporal changes in protist diversity at the Long Term Ecological Research (LTER) station MareChiara in the Gulf of Naples (Mediterranean Sea) on eight dates in 2011 using a metabarcoding approach. Illumina analysis of the V4 and V9 fragments of the 18S rDNA produced 869 522 and 1 410 071 sequences resulting in 6517 and 6519 OTUs, respectively. Marked compositional variations were recorded across the year, with less than 2% of OTUs shared among all samples and similar patterns for the two marker tags. Alveolata, Stramenopiles and Rhizaria were the most represented groups. A comparison with light microscopy data indicated an over-representation of Dinophyta in the sequence dataset, whereas Bacillariophyta showed comparable taxonomic patterns between sequence and light microscopy data. Shannon diversity values were stable from February to September, increasing thereafter with a peak in December. Community variance was mainly explained by seasonality (as temperature), trophic status (as chlorophyll a), and influence of coastal waters (as salinity). Overall, the background knowledge of the system provided a sound context for the result interpretation, showing that LTER sites provide an ideal setting for high-throughput sequencing (HTS) metabarcoding characterisation of protist assemblages and their relationships with environmental variations.

BCR/ABL1 fusion transcripts generated from alternative splicing: implications for future targeted therapies in Ph+ leukaemias.

Philadelphia (Ph+) positive leukaemias are an example of haematological malignant diseases where different chromosomal rearrangements involving both BCR and ABL1 genes generate a variety of chimeric proteins (BCR/ABL1 p210, p190 and p230) which are considered pathological "biomarkers". In addition to these three, there is a variety of fusion transcripts whose origin may depend either on diverse genetic rearrangement or on alternative/atypical splicing of the main mRNAs or on the occurrence of single-point mutations. Although the therapy of Ph+ leukaemias based on Imatinib represents a triumph of medicine, not all patients benefit from such drug and may show resistance and intolerance. Furthermore, interruption of Imatinib administration is often followed by clinical relapse, suggesting a failure in the eradication of residual leukaemic stem cells. Therefore, while the targeted therapy is searching for new and implemented pharmacological inhibitors covering all the possible mutations in the kinase domain, there is urge to identify alternative molecular targets to develop other specific and effective therapeutic approaches. In this review we discuss the importance of recent advances based on the discovery of novel BCR/ABL1 variants and their potential role as new targets/biomarkers of Ph+ leukaemias in the light of the current therapeutic trends. The limits of the pharmacological inhibitors used for treating the disease can be overcome by considering other targets than the kinase enzyme. Our evaluations highlight the potential of alternative perspectives in the therapy of Ph+ leukaemias.

Evolution of the mitochondrial genome of Metazoa as exemplified by comparison of congeneric species.

The mitochondrial genome (mtDNA) of Metazoa is a good model system for evolutionary genomic studies and the availability of more than 1000 sequences provides an almost unique opportunity to decode the mechanisms of genome evolution over a large phylogenetic range. In this paper, we review several structural features of the metazoan mtDNA, such as gene content, genome size, genome architecture and the new parameter of gene strand asymmetry in a phylogenetic framework. The data reviewed here show that: (1) the plasticity of Metazoa mtDNA is higher than previously thought and mainly due to variation in number and location of tRNA genes; (2) an exceptional trend towards stabilization of genomic features occurred in deuterostomes and was exacerbated in vertebrates, where gene content, genome architecture and gene strand asymmetry are almost invariant. Only tunicates exhibit a very high degree of genome variability comparable to that found outside deuterostomes. In order to analyse the genomic evolutionary process at short evolutionary distances, we have also compared mtDNAs of species belonging to the same genus: the variability observed in congeneric species significantly recapitulates the evolutionary dynamics observed at higher taxonomic ranks, especially for taxa showing high levels of genome plasticity and/or fast nucleotide substitution rates. Thus, the analysis of congeneric species promises to be a valuable approach for the assessment of the mtDNA evolutionary trend in poorly or not yet sampled metazoan groups.

ASPicDB: a database resource for alternative splicing analysis.

MOTIVATION: Alternative splicing has recently emerged as a key mechanism responsible for the expansion of transcriptome and proteome complexity in human and other organisms. Although several online resources devoted to alternative splicing analysis are available they may suffer from limitations related both to the computational methodologies adopted and to the extent of the annotations they provide that prevent the full exploitation of the available data. Furthermore, current resources provide limited query and download facilities. RESULTS: ASPicDB is a database designed to provide access to reliable annotations of the alternative splicing pattern of human genes and to the functional annotation of predicted splicing isoforms. Splice-site detection and full-length transcript modeling have been carried out by a genome-wide application of the ASPic algorithm, based on the multiple alignments of gene-related transcripts (typically a Unigene cluster) to the genomic sequence, a strategy that greatly improves prediction accuracy compared to methods based on independent and progressive alignments. Enhanced query and download facilities for annotations and sequences allow users to select and extract specific sets of data related to genes, transcripts and introns fulfilling a combination of user-defined criteria. Several tabular and graphical views of the results are presented, providing a comprehensive assessment of the functional implication of alternative splicing in the gene set under investigation. ASPicDB, which is regularly updated on a monthly basis, also includes information on tissue-specific splicing patterns of normal and cancer cells, based on available EST sequences and their library source annotation. AVAILABILITY: www.caspur.it/ASPicDB

Statistical assessment of functional categories of genes deregulated in pathological conditions by using microarray data.

MOTIVATION: A major challenge in current biomedical research is the identification of cellular processes deregulated in a given pathology through the analysis of gene expression profiles. To this end, predefined lists of genes, coding specific functions, are compared with a list of genes ordered according to their values of differential expression measured by suitable univariate statistics. RESULTS: We propose a statistically well-founded method for measuring the relevance of predefined lists of genes and for assessing their statistical significance starting from their raw expression levels as recorded on the microarray. We use prediction accuracy as a measure of relevance of the list. The rationale is that a functional category, coded through a list of genes, is perturbed in a given pathology if it is possible to correctly predict the occurrence of the disease in new subjects on the basis of the expression levels of the genes belonging to the list only. The accuracy is estimated with multiple random validation strategy and its statistical significance is assessed against a couple of null hypothesis, by using two independent permutation tests. The utility of the proposed methodology is illustrated by analyzing the relevance of Gene Ontology terms belonging to biological process category in colon and prostate cancer, by using three different microarray data sets and by comparing it with current approaches. AVAILABILITY: Source code for the algorithms is available from author upon request. SUPPLEMENTARY INFORMATION: Colon cancer data set and a complete description of experimental results are available at: ftp://bioftp:76bioftpxxx@marx.ba.issia.cnr.it/supp-info.htm.

On the statistical assessment of classifiers using DNA microarray data.

BACKGROUND: In this paper we present a method for the statistical assessment of cancer predictors which make use of gene expression profiles. The methodology is applied to a new data set of microarray gene expression data collected in Casa Sollievo della Sofferenza Hospital, Foggia--Italy. The data set is made up of normal (22) and tumor (25) specimens extracted from 25 patients affected by colon cancer. We propose to give answers to some questions which are relevant for the automatic diagnosis of cancer such as: Is the size of the available data set sufficient to build accurate classifiers? What is the statistical significance of the associated error rates? In what ways can accuracy be considered dependant on the adopted classification scheme? How many genes are correlated with the pathology and how many are sufficient for an accurate colon cancer classification? The method we propose answers these questions whilst avoiding the potential pitfalls hidden in the analysis and interpretation of microarray data. RESULTS: We estimate the generalization error, evaluated through the Leave-K-Out Cross Validation error, for three different classification schemes by varying the number of training examples and the number of the genes used. The statistical significance of the error rate is measured by using a permutation test. We provide a statistical analysis in terms of the frequencies of the genes involved in the classification. Using the whole set of genes, we found that the Weighted Voting Algorithm (WVA) classifier learns the distinction between normal and tumor specimens with 25 training examples, providing e = 21% (p = 0.045) as an error rate. This remains constant even when the number of examples increases. Moreover, Regularized Least Squares (RLS) and Support Vector Machines (SVM) classifiers can learn with only 15 training examples, with an error rate of e = 19% (p = 0.035) and e = 18% (p = 0.037) respectively. Moreover, the error rate decreases as the training set size increases, reaching its best performances with 35 training examples. In this case, RLS and SVM have error rates of e = 14% (p = 0.027) and e = 11% (p = 0.019). Concerning the number of genes, we found about 6000 genes (p < 0.05) correlated with the pathology, resulting from the signal-to-noise statistic. Moreover the performances of RLS and SVM classifiers do not change when 74% of genes is used. They progressively reduce up to e = 16% (p < 0.05) when only 2 genes are employed. The biological relevance of a set of genes determined by our statistical analysis and the major roles they play in colorectal tumorigenesis is discussed. CONCLUSIONS: The method proposed provides statistically significant answers to precise questions relevant for the diagnosis and prognosis of cancer. We found that, with as few as 15 examples, it is possible to train statistically significant classifiers for colon cancer diagnosis. As for the definition of the number of genes sufficient for a reliable classification of colon cancer, our results suggest that it depends on the accuracy required.

Discovery of 342 putative new genes from the analysis of 5'-end-sequenced full-length-enriched cDNA human transcripts.

In this work we describe the process that, starting with the production of human full-length-enriched cDNA libraries using the CAP-Trapper method, led us to the discovery of 342 putative new human genes. Twenty-three thousand full-length-enriched clones, obtained from various cell lines and tissues in different developmental stages, were 5'-end sequenced, allowing the identification of a pool of 5300 unique cDNAs. By comparing these sequences to various human and vertebrate nucleotide databases we found that about 40% of our clones extended previously annotated 5' ends, 662 clones were likely to represent splice variants of known genes, and finally 342 clones remained unknown, with no or poor functional annotation. cDNA-microarray gene expression analysis showed that 260 of 342 unknown clones are expressed in at least one cell line and/or tissue. Further analysis of their sequences and the corresponding genomic locations allowed us to conclude that most of them represent potential novel genes, with only a small fraction having protein-coding potential.

GeneSyn: a tool for detecting conserved gene order across genomes.

UNLABELLED: GeneSyn is a software tool that allows automatic detection of conserved gene order from annotated genomes. AVAILABILITY: Available free of charge for Unix/Linux/Cygwin platforms at ftp://159.149.110.11/pub/GeneSyn_1.0/ SUPPLEMENTARY INFORMATION: ftp://159.149.110.11/pub/GeneSyn_1.0/

The estimation of relative site variability among aligned homologous protein sequences.

MOTIVATION: Maximum likelihood-based methods to estimate site by site substitution rate variability in aligned homologous protein sequences rely on the formulation of a phylogenetic tree and generally assume that the patterns of relative variability follow a pre-determined distribution. We present a phylogenetic tree-independent method to estimate the relative variability of individual sites within large datasets of homologous protein sequences. It is based upon two simple assumptions. Firstly that substitutions observed between two closely related sequences are likely, in general, to occur at the most variable sites. Secondly that non-conservative amino acid substitutions tend to occur at more variable sites. Our methodology makes no assumptions regarding the underlying pattern of relative variability between sites. RESULTS: We have compared, using data simulated under a non-gamma distributed model, the performance of this approach to that of a maximum likelihood method that assumes gamma distributed rates. At low mean rates of evolution our method inferred site by site relative substitution rates more accurately than the maximum likelihood approach in the absence of prior assumptions about the relationships between sequences. Our method does not directly account for the effects of mutational saturation, However, we have incorporated an 'ad-hoc' modification that allows the accurate estimation of relative site variability in fast evolving and saturated datasets.

Structural and functional features of eukaryotic mRNA untranslated regions.

The crucial role of the non-coding portion of genomes is now widely acknowledged. In particular, mRNA untranslated regions are involved in many post-transcriptional regulatory pathways that control mRNA localization, stability and translation efficiency. We review in this paper the major structural and compositional features of eukaryotic mRNA untranslated regions and provide some examples of bioinformatic analyses for their functional characterization.

An algorithm for finding signals of unknown length in DNA sequences.

Pattern discovery in unaligned DNA sequences is a challenging problem in both computer science and molecular biology. Several different methods and techniques have been proposed so far, but in most of the cases signals in DNA sequences are very complicated and avoid detection. Exact exhaustive methods can solve the problem only for short signals with a limited number of mutations. In this work, we extend exhaustive enumeration also to longer patterns. More in detail, the basic version of algorithm presented in this paper, given as input a set of sequences and an error ratio epsilon < 1, finds all patterns that occur in at least q sequences of the set with at most epsilonm mutations, where m is the length of the pattern. The only restriction is imposed on the location of mutations along the signal. That is, a valid occurrence of a pattern can present at most [epsiloni] mismatches in the first i nucleotides, and so on. However, we show how the algorithm can be used also when no assumption can be made on the position of mutations. In this case, it is also possible to have an estimate of the probability of finding a signal according to the signal length, the error ratio, and the input parameters. Finally, we discuss some significance measures that can be used to sort the patterns output by the algorithm.

A novel method for estimating substitution rate variation among sites in a large dataset of homologous DNA sequences.

We present here a novel method to estimate the site-specific relative variability in large sets of homologous sequences. It is based on the simple idea that the more closely related are the compared sequences, the higher the probability of observing nucleotide changes at rapidly evolving sites. A simulation study has been carried out to support the reliability of the method, which has been applied also to analyzing the site variability of all available human sequences corresponding to the two hypervariable regions of the mitochondrial D-loop.