IntroductionClinical genomics promise to be especially suitable for the study of etiologically heterogeneous conditions such as Autism Spectrum Disorder (ASD). Here we present three siblings with ASD where we evaluated the usefulness of Whole Genome Sequencing (WGS) for the diagnostic approach to ASD.MethodsWe identified a family segregating ASD in three siblings with an unidentified cause. We performed WGS in the three probands and used a state-of-the-art comprehensive bioinformatic analysis pipeline and prioritized the identified variants located in genes likely to be related to ASD. We validated the finding by Sanger sequencing in the probands and their parents.ResultsThree male siblings presented a syndrome characterized by severe intellectual disability, absence of language, autism spectrum symptoms and epilepsy with negative family history for mental retardation, language disorders, ASD or other psychiatric disorders. We found germline mosaicism for a heterozygous deletion of a cytosine in the exon 21 of the SHANK3 gene, resulting in a missense sequence of 5 codons followed by a premature stop codon (NM_033517:c.3259_3259delC, p.Ser1088Profs*6).ConclusionsWe reported an infrequent form of familial ASD where WGS proved useful in the clinic. We identified a mutation in SHANK3 that underscores its relevance in Autism Spectrum Disorder.

Cold storage is extensively used to slow the rapid deterioration of peach (Prunus persica L. Batsch) fruit after harvest. However, peach fruit subjected to long periods of cold storage develop chilling injury (CI) symptoms. Post-harvest heat treatment (HT) of peach fruit prior to cold storage is effective in reducing some CI symptoms, maintaining fruit quality, preventing softening and controlling post-harvest diseases. To identify the molecular changes induced by HT, which may be associated to CI protection, the differential transcriptome of peach fruit subjected to HT was characterized by the differential display technique. A total of 127 differentially expressed unigenes (DEUs), with a presence-absence pattern, were identified comparing peach fruit ripening at 20°C with those exposed to a 39°C-HT for 3 days. The 127 DEUs were divided into four expression profile clusters, among which the heat-induced (47%) and heat-repressed (36%) groups resulted the most represented, including genes with unknown function, or involved in protein modification, transcription or RNA metabolism. Considering the CI-protection induced by HT, 23-heat-responsive genes were selected and analyzed during and after short-term cold storage of peach fruit. More than 90% of the genes selected resulted modified by cold, from which nearly 60% followed the same and nearly 40% opposite response to heat and cold. Moreover, by using available Arabidopsis microarray data, it was found that nearly 70% of the peach-heat responsive genes also respond to cold in Arabidopsis, either following the same trend or showing an opposite response. Overall, the high number of common responsive genes to heat and cold identified in the present work indicates that HT of peach fruit after harvest induces a cold response involving complex cellular processes; identifying genes that are involved in the better preparation of peach fruit for cold-storage and unraveling the basis for the CI protection induced by HT.

The human microbiota is the collection of microorganisms living in or on the human body. An imbalance or dysbiosis in these microbial communities can be associated with a wide variety of human diseases (Petersen and Round, 2014; Pham and Lawley, 2014; Zaura et al., 2014). Moreover, when the microbiota of the same body sites is compared between different healthy individuals, specific microbial community features are apparent (Li et al., 2012; Yatsunenko et al., 2012; Oh et al., 2014; Relman, 2015). In addition, specific selective pressures are found at distinct body sites leading to different patterns in microbial community structure and composition (Costello et al., 2009; Consortium, 2012b; Zhou et al., 2013). Because of these natural variations, a comprehensive characterization of the healthy microbiota is critical for predicting alterations related to diseases. This characterization should be based on a broad healthy population over time, geography, and culture (Yatsunenko et al., 2012; Shetty et al., 2013; Leung et al., 2015; Ross et al., 2015). The study of healthy individuals representing different ages, cultural traditions, and ethnic origins will enable to understand how the associated microbiota varies between populations and respond to different lifestyles. It is important to address these natural variations in order to later detect variations related to disease.

Here we present the first dataset based on human microbiota samples of an urban middle-income population in South America. We characterized the microbiota of six different body habitats: palatine tonsils, saliva, buccal mucosa, throat, anterior nares and gut from samples of healthy individual living in a metropolitan area in Argentina. Our initial findings revealed differences in the structure and composition of the microbial communities compared to the US urban population. By sharing our data, we want to actively encourage its reuse for comparison purposes. This will hopefully result in novel biological insights on the variability of the microbiota of healthy individuals across populations worldwide. Moreover, the understanding of the human microbiota ecosystem in a health-associated state will help to answer questions related to the role of the microbiota in disease.