Maximum likelihood estimation of a migration matrix and effective population sizes in n subpopulations by using a coalescent approach

A maximum likelihood estimator based on the coalescent for unequal migration rates and different subpopulation sizes is developed. The method uses a Markov chain Monte Carlo approach to investigate possible genealogies with branch lengths and with migration events. Properties of the new method are shown by using simulated data from a four-population n-island model and a source–sink population model. Our estimation method as coded in migrate is tested against genetree; both programs deliver a very similar likelihood surface. The algorithm converges to the estimates fairly quickly, even when the Markov chain is started from unfavorable parameters. The method was used to estimate gene flow in the Nile valley by using mtDNA data from three human populations.

Using rare mutations to estimate population divergence times: A maximum likelihood approach

In this paper we propose a method to estimate by maximum likelihood the divergence time between two populations, specifically designed for the analysis of nonrecurrent rare mutations. Given the rapidly growing amount of data, rare disease mutations affecting humans seem the most suitable candidates for this method. The estimator RD, and its conditional version RDc, were derived, assuming that the population dynamics of rare alleles can be described by using a birth–death process approximation and that each mutation arose before the split of a common ancestral population into the two diverging populations. The RD estimator seems more suitable for large sample sizes and few alleles, whose age can be approximated, whereas the RDc estimator appears preferable when this is not the case. When applied to three cystic fibrosis mutations, the estimator RD could not exclude a very recent time of divergence among three Mediterranean populations. On the other hand, the divergence time between these populations and the Danish population was estimated to be, on the average, 4,500 or 15,000 years, assuming or not a selective advantage for cystic fibrosis carriers, respectively. Confidence intervals are large, however, and can probably be reduced only by analyzing more alleles or loci.

Complete structure of the human alpha-albumin gene, a new member of the serum albumin multigene family.

The nucleotide sequence of the human alpha-albumin gene, including 887 bp of the 5'-flanking region and 1311 bp of the 3-flanking region (24,454 in total), was determined from three overlapping lambda phage clones. The sequence spans 22,256 bp from the cap site to the polyadenylylation site, revealing a gene structure of 15 exons separated by 14 introns. The methionine initiation codon ATG is within exon 1; the termination codon TGA is within exon 14. Exon 15 is entirely untranslated and contains the polyadenylylation signal AATAAA. The deduced polypeptide chain is composed of a 21-amino-acid leader peptide, followed by 578 amino acids of the mature protein. There are seven repetitive DNA elements (Alu and Kpn) in the introns and 3-flanking region. The sizes of the 15 alpha-albumin exons match closely those of the albumin, alpha-fetoprotein, and vitamin D-binding protein genes. The exons are symmetrically placed within the three domains of the individual proteins, and they share a characteristic codon splitting pattern that is conserved among members of the gene family. The results provide strong evidence that alpha-albumin belongs to, and most likely completes with, the serum albumin gene family. Based on structural similarity, alpha-albumin appears to be most closely related to alpha-fetoprotein. The complete structure of this family of four tandemly linked genes provides a well-characterized approximately 200 kb locus in the 4q subcentromeric region of the human genome.

A maximum likelihood algorithm for genome mapping of cytogenetic loci from meiotic configuration data.

Frequencies of meiotic configurations in cytogenetic stocks are dependent on chiasma frequencies in segments defined by centromeres, breakpoints, and telomeres. The expectation maximization algorithm is proposed as a general method to perform maximum likelihood estimations of the chiasma frequencies in the intervals between such locations. The estimates can be translated via mapping functions into genetic maps of cytogenetic landmarks. One set of observational data was analyzed to exemplify application of these methods, results of which were largely concordant with other comparable data. The method was also tested by Monte Carlo simulation of frequencies of meiotic configurations from a monotelodisomic translocation heterozygote, assuming six different sample sizes. The estimate averages were always close to the values given initially to the parameters. The maximum likelihood estimation procedures can be extended readily to other kinds of cytogenetic stocks and allow the pooling of diverse cytogenetic data to collectively estimate lengths of segments, arms, and chromosomes.