Sequencing and annotated analysis of an Estonian human genome

Genetic interaction between two VNTRs in the MAOA gene is associated with the nicotine dependence

IMPACT STATEMENT

The present study combined the analysis of two transcriptional regulators, uVNTR and dVNTR, in the MAOA gene that is an enzyme responsible for the monoamine degradation and identified genetic interaction between these VNTRs in association with the nicotine dependence. The main impact is that when analyzing different populations in the genetic studies, the functionally meaningful variants should be combined rather than addressing individual elements separately (a mini polygenic risk score for a particular gene/locus). This combination is very rarely analyzed and therefore the study sets an example. Another impact is that we analyzed the genetic variability in the Asian population and therefore our data present a piece of information from underrepresented populations.

The sequencing and interpretation of the genome obtained from a Serbian individual

Recent genetic studies and whole-genome sequencing projects have greatly improved our understanding of human variation and clinically actionable genetic information. Smaller ethnic populations, however, remain underrepresented in both individual and large-scale sequencing efforts and hence present an opportunity to discover new variants of biomedical and demographic significance. This report describes the sequencing and analysis of a genome obtained from an individual of Serbian origin, introducing tens of thousands of previously unknown variants to the currently available pool. Ancestry analysis places this individual in close proximity to Central and Eastern European populations; i.e., closest to Croatian, Bulgarian and Hungarian individuals and, in terms of other Europeans, furthest from Ashkenazi Jewish, Spanish, Sicilian and Baltic individuals. Our analysis confirmed gene flow between Neanderthal and ancestral pan-European populations, with similar contributions to the Serbian genome as those observed in other European groups. Finally, to assess the burden of potentially disease-causing/clinically relevant variation in the sequenced genome, we utilized manually curated genotype-phenotype association databases and variant-effect predictors. We identified several variants that have previously been associated with severe early-onset disease that is not evident in the proband, as well as putatively impactful variants that could yet prove to be clinically relevant to the proband over the next decades. The presence of numerous private and low-frequency variants, along with the observed and predicted disease-causing mutations in this genome, exemplify some of the global challenges of genome interpretation, especially in the context of under-studied ethnic groups.

Sequencing and annotated analysis of full genome of Holstein breed bull

In the present study, we describe the deep sequencing and structural analysis of the Holstein breed bull genome. Our aim was to receive a high-quality Holstein bull genome reference sequence and to describe different types of variations in its genome compared to Hereford breed as a reference. We generated four mate-paired libraries and one fragment library from 30 μg of genomic DNA. Colour space fasta were mapped and paired to the reference cow (Bos taurus) genome assembly from Oct. 2011 (Baylor 4.6.1/bosTau7). Initial sequencing resulted in the 4,864,054,296 of 50-bp reads. Average mapping efficiency was 71.7 % and altogether 3,494,534,136 reads and 157,928,163,086 bp were successfully mapped, resulting in 60 × coverage. This is the highest coverage for bovine genome published so far. Tertiary analysis found 6,362,988 SNPs in the bull's genome, 4,045,889 heterozygous and 2,317,099 homozygous variants. Annotation revealed that 4,330,337 of all discovered SNPs were annotated in the dbSNP database (build 137) and therefore 2,032,651 SNPs were novel. Large indel variations accounted for the 245,947,845 bp of the variation in entire genome and their number was 312,879. We also found that small indels (number was 633,310) accounted for the total variation of 2,542,552 nucleotides in the genome. Only 106,768 small indels were listed in the dbSNP. Finally, we identified 2,758 inversions in the genome of the bull covering in total 23,099,054 bp of genome's variation. The largest inversion was 87,440 bp in size. In conclusion, the present study discovered different types of novel variants in bull's genome after high-coverage sequencing. Better knowledge of the functions of these variations is needed.

Sequencing and annotated analysis of the Holstein cow genome

The aim of our study was to create a high-quality Holstein cow genome reference sequence and describe the different types of variations in this genome compared to the reference Hereford breed. We generated one fragment and three mate-paired libraries from genomic DNA. Raw files were mapped and paired to the reference cow (Bos taurus) genome assemblies bosTau6/UMD_3.1. BioScope (v1.3) software was used for mapping and variant analysis. Initial sequencing resulted in 2,842,744,008 of 50-bp reads. Average mapping efficiency was 78.4 % and altogether 2,168,425,497 reads and 98,022,357,422 bp were successfully mapped, resulting in 36.7X coverage. Tertiary analysis found 5,923,230 SNPs in the bovine genome, of which 3,833,249 were heterozygous and 2,089,981 were homozygous variants. Annotation revealed that 4,241,000 of all discovered SNPs were annotated in the dbSNP database and 1,682,230 SNPs were considered as novel. Large indel variations accounted for 48,537,190 bp of the entire genome and there were 138,504 of them. The largest deletion was 18,594 bp and the largest insertion was 13,498 bp. Another group of variants, small indels (n = 458,061), accounted for the total variation of 1,839,872 nucleotides in the genome. Only 92,115 small indels were listed in the dbSNP and therefore 365,946 small indels were novel. Finally, we identified 1,876 inversions in the bovine genome. In conclusion, this is another description of the Holstein cow genome and, similar to previous studies, we found a large amount of novel variations. Better knowledge of these variations could explain significant phenotypic differences (e.g., health, production, reproduction) between different breeds.