Rapidly Mutating Y Chromosomal STRs in Deep-Rooted Endogamous Pedigrees

Y-chromosome short tandem repeat polymorphisms (Y-STRs) are important in many areas of human genetics. Y chromosomal STRs being normally utilized in the field of forensic exhibit low haplotype diversity in endogamous populations and fail to discriminate among male relatives from same pedigree. Rapidly mutating Y-STRs (RM Y-STRs) have been paid much attention in last decade. These 13 RM Y STRs have high mutation rates (>10-2) and have considerably higher haplotype diversity and discrimination capacity than conventionally used Y-STRs showing remarkable power, when it comes to differentiation in paternal lineages in endogamous populations. Previously, we have analyzed 2–4 generation, 99 pedigrees covering 1568 pairs of men covering 1–6 meioses from all over Pakistan and 216 male relatives from 18 deep rooted endogamous Sindhi pedigrees covering 1-7 meioses. Here we are presenting 861 pairs of men from 63 endogamous pedigrees covering 1-6 meioses from Punjabi population of Punjab, Pakistan. Mutations were frequently observed at DYF399 and DYF403 while no mutation was observed at DYS526a/b. The rate of differentiation ranged from 29.70% (first meiosis) to 80.95% (fifth meiosis) while overall (1 to 6 meiosis) differentiation was 59.46%. Combining previously published data with newly generated data, an overall differentiation rate was 38.79% based on 5176 pairs of men related by 1–20 meioses, while Y-filer differentiation was 9.24% based on 3864 pairs. Using father-son pair data from the present and previous studies, we also provide updated RM Y-STR mutation rates.

Genetic association of anthropometric traits with type 2 diabetes in ethnically endogamous Sindhi families

Background Ethnically endogamous populations can shed light on the genetics of type 2 diabetes. Such studies are lacking in India. We conducted this study to determine the genetic and environmental contributions of anthropometric traits to type 2 diabetes risk in the Sindhi families in central India. Methods We conducted a family study in Indian Sindhi families with at least one case of type 2 diabetes. Variance components methods were used to quantify the genetic association of 18 anthropometric traits with eight type 2 diabetes related traits. Univariate and bivariate polygenic models were used to determine the heritability, genetic and environmental correlation of anthropometric traits with type 2 diabetes related traits. Results We included 1,152 individuals from 112 phenotyped families. The ascertainment-bias corrected prevalence of type 2 diabetes was 35%. Waist circumference, hip circumference and the biceps, triceps, subscapular and medial calf skinfold thicknesses were polygenically and significantly associated with type 2 diabetes. The range of heritability of the anthropometric traits and type 2 diabetes related traits was 0.27–0.73 and 0.00–0.39, respectively. Heritability of type 2 diabetes as a discrete trait was 0.35. Heritability curves demonstrated a substantial local influence of type 2 diabetes related traits. Bivariate trait analyses showed that biceps and abdominal skinfold thickness and all waist-containing indexes were strongly genetically correlated with type 2 diabetes. Conclusions In this first study of Sindhi families, we found evidence for genetic and environmental concordance of anthropometric traits with type 2 diabetes. Future studies need to probe into the genetics of type 2 diabetes in this population.

Ancestral haplotype reconstruction in endogamous populations using identity-by-descent

In this work we develop a novel algorithm for reconstructing the genomes of ancestral individuals, given genotype or sequence data from contemporary individuals and an extended pedigree of family relationships. A pedigree with complete genomes for every individual enables the study of allele frequency dynamics and haplotype diversity across generations, including deviations from neutrality such as transmission distortion. When studying heritable diseases, ancestral haplotypes can be used to augment genome-wide association studies and track disease inheritance patterns. The building blocks of our reconstruction algorithm are segments of Identity-By-Descent (IBD) shared between two or more genotyped individuals. The method alternates between identifying a source for each IBD segment and assembling IBD segments placed within each ancestral individual. Unlike previous approaches, our method is able to accommodate complex pedigree structures with hundreds of individuals genotyped at millions of SNPs. We apply our method to an Old Order Amish pedigree from Lancaster, Pennsylvania, whose founders came to the United States from Europe during the early 18th century. The pedigree includes 1338 individuals from the past 12 generations, 394 with genotype data. The motivation for reconstruction is to understand the genetic basis of diseases segregating in the family through tracking haplotype transmission over time. Using our algorithm thread, we are able to reconstruct an average of 224 ancestral individuals per chromosome. For these ancestral individuals, on average we reconstruct 79% of their haplotypes. We also identify a region on chromosome 16 that is difficult to reconstruct—we find that this region harbors a short Amish-specific copy number variation and the gene HYDIN. thread was developed for endogamous populations, but can be applied to any extensive pedigree with the recent generations genotyped. We anticipate that this type of practical ancestral reconstruction will become more common and necessary to understand rare and complex heritable diseases in extended families.

A rapid, accurate approach to inferring pedigrees in endogamous populations

Accurate reconstruction of pedigrees from genetic data remains a challenging problem. Pedigree inference algorithms are often trained only on urban European-descent families, which are comparatively ‘outbred’ compared to many other global populations. Relationship categories can be difficult to distinguish (e.g. half-sibships versus avuncular) without external information. Furthermore, published software cannot accommodate endogamous populations where there may be reticulations within a pedigree or elevated haplotype sharing. We design a simple, rapid algorithm which initially uses only high-confidence first degree relationships to seed a machine learning step based on the number of identical by descent segments. Additionally, we define a new statistic to polarize individuals to ancestor versus descendant generation. We test our approach in a sample of 700 individuals from northern Namibia, sampled from an endogamous population. Due to a culture of concurrent relationships in this population, there is a high proportion of half-sibships. We accurately identify first through third degree relationships for all categories, including half-sibships, half-avuncular-ships etc. We further validate our approach in the Barbados Asthma Genetics Study (BAGS) dataset. Accurate reconstruction of pedigrees holds promise for tracing allele frequency trajectories, improved phasing and other population genomic questions.

Ancestral Haplotype Reconstruction in Endogamous Populations using Identity-By-Descent

In this work we develop a novel algorithm for reconstructing the genomes of ancestral individuals, given genotype or sequence data from contemporary individuals and an extended pedigree of family relationships. A pedigree with complete genomes for every individual enables the study of allele frequency dynamics and haplotype diversity across generations, including deviations from neutrality such as transmission distortion. When studying heritable diseases, ancestral haplotypes can be used to augment genome-wide association studies and track disease inheritance patterns. The building blocks of our reconstruction algorithm are segments of Identity-By-Descent (IBD) shared between two or more genotyped individuals. The method alternates between identifying a source for each IBD segment and assembling IBD segments placed within each ancestral individual. Unlike previous approaches, our method is able to accommodate complex pedigree structures with hundreds of individuals genotyped at millions of SNPs.We apply our method to an Old Order Amish pedigree from Lancaster, Pennsylvania, whose founders came to the United States from Europe during the early 18th century. The pedigree includes 1338 individuals from the past 10 generations, 394 with genotype data. The motivation for reconstruction is to understand the genetic basis of diseases segregating in the family through tracking haplotype transmission over time. Using our algorithm thread, we are able to reconstruct an average of 224 ancestral individuals per chromosome. For these ancestral individuals, on average we reconstruct 79% of their haplotypes. We also identify a region on chromosome 16 that is difficult to reconstruct – we find that this region harbors a short Amish-specific copy number variation and the gene HYDIN. thread was developed for endogamous populations, but can be applied to any extensive pedigree with the recent generations genotyped. We anticipate that this type of practical ancestral reconstruction will become more common and necessary to understand rare and complex heritable diseases in extended families.Author summaryWhen analyzing complex heritable traits, it is often useful to have genomic data from many generations of an extended family, to increase the amount of information available for statistical inference. However, we typically only have genomic data from the recent generations of a pedigree, as ancestral individuals are deceased. In this work we present an algorithm, called thread, for reconstructing the genomes of ancestral individuals, given a complex pedigree and genomic data from the recent generations. Previous approaches have not been able to accommodate large datasets (both in terms of sites and individuals), made simplifying assumptions about pedigree structure, or did not tie reconstructed sequences back to specific individuals. We apply thread to a complex Old Order Amish pedigree of 1338 individuals, 394 with genotype data.

MBL2Variations and Malaria Susceptibility in Indian Populations

ABSTRACTHuman mannose-binding lectin (MBL) encoded by theMBL2gene is a pattern recognition protein and has been associated with many infectious diseases, including malaria. We sought to investigate the contribution of functionalMBL2gene variations toPlasmodium falciparummalaria in well-defined cases and in matched controls. We resequenced the 8.7 kb of the entireMBL2gene in 434 individuals clinically classified with malaria from regions of India where malaria is endemic. The study cohort included 176 patients with severe malaria, 101 patients with mild malaria, and 157 ethnically matched asymptomatic individuals. In addition, 830 individuals from 32 socially, linguistically, and geographically diverse endogamous populations of India were investigated for the distribution of functionalMBL2variants. TheMBL2 −221C(X) allelic variant is associated with increased risk of malaria (mild malaria odds ratio [OR] = 1.9, correctedPvalue [PCorr] = 0.0036; severe malaria OR = 1.6,PCorr= 0.02). The exon1 variantsMBL2*B(severe malaria OR = 2.1,PCorr= 0.036; mild versus severe malaria OR = 2.5,PCorr= 0.039) andMBL2*C(mild versus severe malaria OR = 5.4,PCorr= 0.045) increased the odds of having malaria. The exon1MBL2*D/*B/*Cvariant increased the risk for severe malaria (OR = 3.4,PCorr= 0.000045). The frequencies of low MBL haplotypes were significantly higher in severe malaria (14.2%) compared to mild malaria (7.9%) and asymptomatic (3.8%). TheMBL2*LYPAhaplotypes confer protection, whereasMBL2*LXPAincreases the malaria risk. Our findings in Indian populations demonstrate thatMBL2functional variants are strongly associated with malaria and infection severity.