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Background: Parthenocarpy is an important trait for yield and quality in many plants. But due to its complex interactions with genetic and physiological factors, it has not been adequately understood and applied to breeding and production. Finding novel and effective quantitative trait loci (QTLs) is a critical step towards understanding its genetic mechanism. Cucumber (Cucumis sativus L.) is a typical parthenocarpic plant but the QTLs controlling parthenocarpy in cucumber were not mapped on chromosomes, and the linked markers were neither user-friendly nor confirmed by previous studies. Hence, we conducted a two-season QTL study of parthenocarpy based on the cucumber genome with 145 F2:3 families derived from a cross between EC1 (a parthenocarpic inbred line) and 8419 s-1 (a non-parthenocarpic inbred line) in order to map novel QTLs. Whole genome re-sequencing was also performed both to develop effective linked markers and to predict candidate genes., Results: A genetic linkage map, employing 133 Simple Sequence Repeats (SSR) markers and nine Insertion/Deletion (InDel) markers spanning 808.1 cM on seven chromosomes, was constructed from an F2 population. Seven novel QTLs were identified on chromosomes 1, 2, 3, 5 and 7. Parthenocarpy 2.1 (Parth2.1), a QTL on chromosome 2, was a major-effect QTL with a logarithm of odds (LOD) score of 9.0 and phenotypic variance explained (PVE) of 17.0 % in the spring season and with a LOD score of 6.2 and PVE of 10.2 % in the fall season. We confirmed this QTL using a residual heterozygous line97-5 (RHL97-5). Effectiveness of linked markers of the Parth2.1 was validated in F3:4 population and in 21 inbred lines. Within this region, there were 57 genes with nonsynonymous SNPs/InDels in the coding sequence. Based on further combined analysis with transcriptome data between two parents, CsARF19, CsWD40, CsEIN1, CsPPR, CsHEXO3, CsMDL, CsDJC77 and CsSMAX1 were predicted as potential candidate genes controlling parthenocarpy., Conclusions: A major-effect QTL Parth2.1 and six minor-effect QTLs mainly contribute to the genetic architecture of parthenocarpy in cucumber. SSR16226 and Indel-T-39 can be used in marker-assisted selection (MAS) of cucumber breeding. Whole genome re-sequencing enhances the efficiency of polymorphic marker development and prediction of candidate genes.

Apple (Malus domestica Borkh.) is a commercially important fruit worldwide. Detailed information on genomic DNA polymorphisms, which are important for understanding phenotypic traits, is lacking for the apple. We re-sequenced two elite apple varieties, 'Nagafu No. 2' and 'Qinguan,' which have different characteristics. We identified many genomic variations, including 2,771,129 single nucleotide polymorphisms (SNPs), 82,663 structural variations (SVs), and 1,572,803 insertion/deletions (INDELs) in 'Nagafu No. 2' and 2,262,888 SNPs, 63,764 SVs, and 1,294,060 INDELs in 'Qinguan.' The 'SNP,' 'INDEL,' and 'SV' distributions were non-random, with variation-rich or -poor regions throughout the genomes. In 'Nagafu No. 2' and 'Qinguan' there were 171,520 and 147,090 non-synonymous SNPs spanning 23,111 and 21,400 genes, respectively; 3,963 and 3,196 SVs in 3,431 and 2,815 genes, respectively; and 1,834 and 1,451 INDELs in 1,681 and 1,345 genes, respectively. Genetic linkage maps of 190 flowering genes associated with multiple flowering pathways in 'Nagafu No. 2,' 'Qinguan,' and 'Golden Delicious,' identified complex regulatory mechanisms involved in floral induction, flower bud formation, and flowering characteristics, which might reflect the genetic variation of the flowering genes. Expression profiling of key flowering genes in buds and leaves suggested that the photoperiod and autonomous flowering pathways are major contributors to the different floral-associated traits between 'Nagafu No. 2' and 'Qinguan.' The genome variation data provided a foundation for the further exploration of apple diversity and gene-phenotype relationships, and for future research on molecular breeding to improve apple and related species.

Advances in de novo sequencing technologies allow us to track deeper insights into microbial genomes for restructuring events during the course of their evolution inside and outside the host. Bacterial species belonging to Ochrobactrum genus are being reported as emerging, and opportunistic pathogens in this technology driven era probably due to insertion and deletion of genes. The Ochrobactrum intermedium M86 was isolated in 2005 from a case of non-ulcer dyspeptic human stomach followed by its first draft genome sequence in 2009. Here we report re-sequencing of O. intermedium M86 laboratory adapted strain in terms of gain and loss of genes. We also attempted for finer scale genome sequence with 10 times more genome coverage than earlier one followed by comparative evaluation on Ion PGM and Illumina MiSeq. Despite their similarities at genomic level, lab-adapted strain mainly lacked genes encoding for transposase protein, insertion elements family, phage tail-proteins that were not detected in original strain on both chromosomes. Interestingly, a 5 kb indel was detected in chromosome 2 that was absent in original strain mapped with phage integrase gene of Rhizobium spp. and may be acquired and integrated through horizontal gene transfer indicating the gene loss and gene gain phenomenon in this genus. Majority of indel fragments did not match with known genes indicating more bioinformatic dissection of this fragment. Additionally we report genes related to antibiotic resistance, heavy metal tolerance in earlier and re-sequenced strain. Though SNPs detected, there did not span urease and flagellar genes. We also conclude that third generation sequencing technologies might be useful for understanding genomic architecture and re-arrangement of genes in the genome due to their ability of larger coverage that can be used to trace evolutionary aspects in microbial system.

Selective sweep can cause genetic differentiation across populations, which allows for the identification of possible causative regions/genes underlying important traits. The pig has experienced a long history of allele frequency changes through artificial selection in the domestication process. We obtained an average of 329,482,871 sequence reads for 24 pigs from three pig breeds: Yorkshire (n = 5), Landrace (n = 13), and Duroc (n = 6). An average read depth of 11.7 was obtained using whole-genome resequencing on an Illumina HiSeq2000 platform. In this study, cross-population extended haplotype homozygosity and cross-population composite likelihood ratio tests were implemented to detect genes experiencing positive selection for the genome-wide resequencing data generated from three commercial pig breeds. In our results, 26, 7, and 14 genes from Yorkshire, Landrace, and Duroc, respectively were detected by two kinds of statistical tests. Significant evidence for positive selection was identified on genes ST6GALNAC2 and EPHX1 in Yorkshire, PARK2 in Landrace, and BMP6, SLA-DQA1, and PRKG1 in Duroc.These genes are reportedly relevant to lactation, reproduction, meat quality, and growth traits. To understand how these single nucleotide polymorphisms (SNPs) related positive selection affect protein function, we analyzed the effect of non-synonymous SNPs. Three SNPs (rs324509622, rs80931851, and rs80937718) in the SLA-DQA1 gene were significant in the enrichment tests, indicating strong evidence for positive selection in Duroc. Our analyses identified genes under positive selection for lactation, reproduction, and meat-quality and growth traits in Yorkshire, Landrace, and Duroc, respectively.

Polymorphism discovery is a routine application of next-generation sequencing technology where multiple samples are sent to a service provider for library preparation, subsequent sequencing, and bioinformatic analyses. The decreasing cost and advances in multiplexing approaches have made it possible to analyze hundreds of samples at a reasonable cost. However, because of the manual steps involved in the initial processing of samples and handling of sequencing equipment, cross-contamination remains a significant challenge. It is especially problematic in cases where polymorphism frequencies do not adhere to diploid expectation, for example, heterogeneous tumor samples, organellar genomes, as well as during bacterial and viral sequencing. In these instances, low levels of contamination may be readily mistaken for polymorphisms, leading to false results. Here we describe practical steps designed to reliably detect contamination and uncover its origin, and also provide new, Galaxy-based, readily accessible computational tools and workflows for quality control. All results described in this report can be reproduced interactively on the web as described at http://usegalaxy.org/contamination.