Millions of people today have access to their personal genomic information. Direct-to-consumer services and integration with other “, big data”,increasingly commoditize what was rightly celebrated as a singular achievement in February 2001 when the first draft human GENOMEs were published. But such remarkable technical and scientific progress has not been without its share of missteps and growing pains. Science invited the experts below to help explore how we got here and where we should (or ought not) be going.

The successful completion of Human GENOME Project (HGP) on April 2003 revolutionized the efforts to understand the biological pathways involved in mental illness and to develop better methods for prevention, diagnosis, and treatment. Previous researches on genes involved in mental illnesses were concentrated on neurotransmitters and their receptors. However, the focus is now expanding and recent analyses show more than 15,000 genes are active in the mammalian brain. Mapping and sequencing data from HGP have accelerated the discovery of genes responsible of single gene disorders. However, there are not single-gene models for common disorders like mental illnesses, cardiovascular disease and cancer. The risk of developing these disorders is thought to be influenced by different factors including one or more genes, lifestyle and environmental factors. To identify the genetic variation associated with complex disorders like mental illnesses and variation in response to drugs the HapMap project has been launched. Different studies on genomic variations (single nucleotide polymorphism [SNP] and copy number variation [CNV]) in large populations affected with disorders including, schizophrenia, depression, and bipolar disorders are underway. For example, in recent years studies on large populations have linked increased risk of schizophrenia to certain variant of Neuregulin 1 gene. The identification of a gene is the first step in long road toward better diagnostic tests, drug therapies and prevention strategies. Research in this emerging field and examine the genomic information can help the patients affected with mental illnesses to have better specific treatment protocols with fewer side effects.

Objective Evaluation and conservation of native chickens as valuable genomic resources is essential. This is the first study for discovering variants in Lari chicken by whole GENOME sequencing data. The study of genetic diversity of Lari chicken at genomic level can provide useful information for its preservation and breeding. In this study, genomic diversity of five Lari individuals was investigated using whole GENOME sequencing technique. Materials and methods Blood samples were taken from five Lari chickens from cites of Shiraz and Zabol, Iran. Whole GENOME sequencing (paired end sequencing) was done by Illumina Company )Hiseq 2500). Data quality was determined by FastQC program. Whole GENOME sequencing data were aligned with chicken GENOME reference (Gallus_gallus-5. 0/galGal5) using MEM algorithm applied in burrows wheeler aligner program (BWA). Processing of bam files was done in several steps. PCR duplicates were removed using Picard program. The Percentage of alignment with the reference GENOME and coverage or depth were calculated using the flagstat and depth commands in samtools software. Single nucleotide polymorphisms (SNPs) and small insertions and deletions (INDELs) were identified by the genomic analysis toolkit (GATK) program. Annotation of SNPs and Indels was done using SnpEff program. Genetic diversity of five chicken GENOMEs was calculated with VCFtools. Results The mean percentage mapping of short sequences with the reference GENOME was 99. 85% and the mean coverage depth was 7. 65 X. In this study, 9. 8 million SNPs and 10 million Indels were identified with the most counts of them in the intron and intergenic regions. The mean of observed and expected heterozygosity percentages for SNPs in five chicken GENOMEs were 0. 30 and 0. 35, respectively. Conclusions Results from annotation showed that percentage of silent SNPs (74. 38%) is higher than that nonsynomous SNPs (missense and nonsense, 25. 62%) in Lari chicken GENOME. The lower observed genetic diversity than the expected genetic diversity, can be due to the forces such as inbreeding in the population of Lari chicken. The information provided herein can be useful for breed conservation and breeding programs and population structure survey.

Objective Evaluation and conservation of native chickens as future genomic resources are essential. In this study, genomic diversity of four Marandi breeds was investigated using whole GENOME sequencing technique. Materials and Methods Blood samples were taken from four chickens in East Azerbaijan province, Iran. Whole GENOME sequencing (paired end sequencing) was done by Illumina Company (Hiseq 2500). Data quality control was performed by FastQC program. Whole GENOME sequencing data were aligned with GENOME reference (Gallus_gallus-5. 0/galGal5) using MEM algorithm implemented in burrows wheeler aligner program (BWA). Single nucleotide polymorphisms (SNPs) and small insertions and deletions (INDELs) were identified by the GATK program. Annotation of SNPs and Indels was done using SnpEff program. Genetic diversity of 4 chicken GENOMEs was calculated with VCFtools. Results The short sequences were compared with the reference GENOME of over 99% and with the mean depth of 7X coverage. In this study, 8. 7 million SNPs and 9. 1 Indels were identified with the most counts of them in the intron and intergenic regions. The mean of observed and expected heterozygosity percentages for SNPs in four chicken GENOMEs were 0. 33 and 0. 35, respectively. Conclusion Results from annotation showed that percentage of the silent SNPs (74. 64%) is higher than that the nonsynomous SNPs (missense and nonsense) in Marandi chicken GENOME. The results obtained from this research can be useful for Marandi chicken breeding and conservation programs.

The impact of genetics on human disorders in 80’s has changed the research as well as therapeutic approaches toward genetic characteristic and discovery of molecular basis of disease in 90’s. Molecular characteristics of less than 80 disorders have been identified up to 1990, while the research has revoked and in 1991 alone more than 83 disorders have been molecularly characterized. These findings engaged the scientific community to complete human GENOME sequence in 2001. However, the GENOME data failed to reveal all the functions as well as change in disease pathology. Thus, post-GENOME era started to explore the function, modification as well as alteration in transcription, metabolism and protein content on the course of disease progress. Therefore, transcriptomics, proteomics and metabolomics as well as functional genomics have been engaged to advance the knowledge on the GENOME-function relationship, protein function to shed light on the molecular basis of disease to target multifactor disordered for molecular treatments. The discovery of the causes of mental disorders to prevent and/or treat these disorders has been a long lasting labor intensive investigation. Since, the multiparametic nature of these disorders and lack of animal model render the pace of research. The spectacular increase in the amount of genomic information provides a remarkable impact on the way that medicine is practiced. Fortunately, with the information of human GENOME as well as post GENOME investigations, there are possibilities to identify the molecular basis of mental disorders and find a better therapeutic approach in the future.