The Genetics of Bene Israel from India Reveals Both Substantial Jewish and Indian Ancestry

The Bene Israel Jewish community from West India is a unique population whose history before the 18^th century remains largely unknown. Bene Israel members consider themselves as descendants of Jews, yet the identity of Jewish ancestors and their arrival time to India are unknown, with speculations on arrival time varying between the 8th century BCE and the 6th century CE. Here, we characterize the genetic history of Bene Israel by collecting and genotyping 18 Bene Israel individuals. Combining with 486 individuals from 41 other Jewish, Indian and Pakistani populations, and additional individuals from worldwide populations, we conducted comprehensive genome-wide analyses based on F_ST, principal component analysis, ADMIXTURE, identity-by-descent sharing, admixture linkage disequilibrium decay, haplotype sharing and allele sharing autocorrelation decay, as well as contrasted patterns between the X chromosome and the autosomes. The genetics of Bene Israel individuals resemble local Indian populations, while at the same time constituting a clearly separated and unique population in India. They are unique among Indian and Pakistani populations we analyzed in sharing considerable genetic ancestry with other Jewish populations. Putting together the results from all analyses point to Bene Israel being an admixed population with both Jewish and Indian ancestry, with the genetic contribution of each of these ancestral populations being substantial. The admixture took place in the last millennium, about 19–33 generations ago. It involved Middle-Eastern Jews and was sex-biased, with more male Jewish and local female contribution. It was followed by a population bottleneck and high endogamy, which can lead to increased prevalence of recessive diseases in this population. This study provides an example of how genetic analysis advances our knowledge of human history in cases where other disciplines lack the relevant data to do so.     

Systematic Dissection of the Sequence Determinants of Gene 3’ End Mediated Expression Control

The 3’end genomic region encodes a wide range of regulatory process including mRNA stability, 3’ end processing and translation. Here, we systematically investigate the sequence determinants of 3’ end mediated expression control by measuring the effect of 13,000 designed 3’ end sequence variants on constitutive expression levels in yeast. By including a high resolution scanning mutagenesis of more than 200 native 3’ end sequences in this designed set, we found that most mutations had only a mild effect on expression, and that the vast majority (~90%) of strongly effecting mutations localized to a single positive TA-rich element, similar to a previously described 3’ end processing efficiency element, and resulted in up to ten-fold decrease in expression. Measurements of 3’ UTR lengths revealed that these mutations result in mRNAs with aberrantly long 3’UTRs, confirming the role for this element in 3’ end processing. Interestingly, we found that other sequence elements that were previously described in the literature to be part of the polyadenylation signal had a minor effect on expression. We further characterize the sequence specificities of the TA-rich element using additional synthetic 3’ end sequences and show that its activity is sensitive to single base pair mutations and strongly depends on the A/T content of the surrounding sequences. Finally, using a computational model, we show that the strength of this element in native 3’ end sequences can explain some of their measured expression variability (R = 0.41). Together, our results emphasize the importance of efficient 3’ end processing for endogenous protein levels and contribute to an improved understanding of the sequence elements involved in this process.     

Functional restitution of cardiac control in heart transplant patients

Cardiovascular control is fundamentally altered after heart transplantation (HT) because of surgical denervation of the heart. The main goal of this work was the noninvasive characterization of cardiac rate control mechanisms after HT and the understanding of their nature. We obtained 25 recordings from 13 male HT patients [age = 28-68 yr, time after transplant (TAT) = 0.5-62.5 mo]. The control group included 14 healthy men (age = 28-59 yr). Electrocardiogram, continuous blood pressure (BP), and respiration were recorded for 45 min in the supine position and then during active change of posture (CP) to standing. The signals were analyzed in the time domain [mean and variance of heart rate (HR) and rise time of HR in response to CP] and the frequency domain [low and high frequency (LF and HF)]. Our principal finding was the consistent pattern of evolution of the HR response to standing: from no response, via a slow response (>40 s, TAT > 6 wk), to a fast increase (<20 s, TAT > 24 mo). HR response correlated with TAT (P < 0.001). LF correlated with HR response to CP (P < 0.0001); HF and HR did not. An important finding was the presence of very-high-frequency peaks in the power spectrum of HR and BP fluctuations. Extensive arrhythmias tended to appear at the TAT that corresponds to the transition from slow to fast HR response to CP. Our results indicate a biphasic evolution in cardiac control mechanisms from lack of control to a first-order control loop followed by partial sympathetic reinnervation and, finally, the direct effect of the old sinoatrial node on the pacemaker cell of the new sinoatrial node. There was no indication of vagal reinnervation.     

Molecular characterization and genetic mapping of two clusters of genes encoding chlorophyll a/b-binding proteins in Lycopersicon esculentum (tomato)

We have constructed a tomato genomic library in the λ Charon 4 phage vector. The library was screened with a pea cDNA probe encoding a chlorophyll a/b-binding protein (CAB), and several recombinant phages containing tomato CAB genes were isolated and characterized by restriction mapping, heteroduplex analysis and nucleotide sequencing. Two phages with overlapping segments of the tomato genome contain a total of four CAB genes, all arranged in tandem. A third phage contains three CAB genes, two arranged in tandem and one in opposite orientation, and an additional, truncated CAB gene. Genetic mapping experiments showed that the four CAB genes on the first two phages belong to a locus, previously designated Cab-1, on chromosome 2. The CAB genes from the third phage belong to the Cab-3 locus on chromosome 3. Complete sequence determination of two CAB genes, one from each locus, and additional sequence determination of about 50% of each of the other five CAB genes showed that each gene within a CAB locus is more similar to other CAB genes in the same locus than it is to the CAB genes from the second locus. Furthermore, the polypeptides encoded by Cab-1 genes diverge significantly from those encoded by Cab-3 genes in the domains of transit peptide and the N terminus of the mature polypeptide but are essentially identical in the rest of the sequence.     

A pair-to-pair amino acids substitution matrix and its applications for protein structure prediction

We present a new structurally derived pair-to-pair substitution matrix (P2PMAT). This matrix is constructed from a very large amount of integrated high quality multiple sequence alignments (Blocks) and protein structures. It evaluates the likelihoods of all 160,000 pair-to-pair substitutions. P2PMAT matrix implicitly accounts for evolutionary conservation, correlated mutations, and residue-residue contact potentials. The usefulness of the matrix for structural predictions is shown in this article. Predicting protein residue-residue contacts from sequence information alone, by our method (P2PConPred) is particularly accurate in the protein cores, where it performs better than other basic contact prediction methods (increasing accuracy by 25-60%). The method mean accuracy for protein cores is 24% for 59 diverse families and 34% for a subset of proteins shorter than 100 residues. This is above the level that was recently shown to be sufficient to significantly improve ab initio protein structure prediction. We also demonstrate the ability of our approach to identify native structures within large sets of (300-2000) protein decoys. On the basis of evolutionary information alone our method ranks the native structure in the top 0.3% of the decoys in 4/10 of the sets, and in 8/10 of sets the native structure is ranked in the top 10% of the decoys. The method can, thus, be used to assist filtering wrong models, complementing traditional scoring functions.     

InSite: a computational method for identifying protein-protein interaction binding sites on a proteome-wide scale

We propose InSite, a computational method that integrates high-throughput protein and sequence data to infer the specific binding regions of interacting protein pairs. We compared our predictions with binding sites in Protein Data Bank and found significantly more binding events occur at sites we predicted. Several regions containing disease-causing mutations or cancer polymorphisms in human are predicted to be binding for protein pairs related to the disease, which suggests novel mechanistic hypotheses for several diseases.