NEW YORK (GenomeWeb News) – In the early, online edition of the Proceedings of the National Academy of Science, North Carolina State University researchers described findings from three related genome-wide association analyses performed using the Drosophila melanogaster Genome Reference Panel, or DGRP, a set of sequenced, inbred fruit fly lines generated from wild Drosophila representatives.
The team focused their attention on genetic factors related to variable olfactory-related behaviors exhibited by flies in the DGRP and in outbred fruit flies selected from the olfactory extremes of the DGRP group. Together, the SNP and quantitative trait loci analyses pointed to a particularly pronounced role for neural development and signaling-related genes in the fruit flies' olfactory variation — a connection that researchers verified through their follow-up gene expression experiments and mutational analyses.
"[D]ifferent elements of the genetic architecture that underlies natural variation in olfactory behavior are revealed in the three [genome-wide association] analyses," senior authors Trudy Mackay and Robert Anholt wrote, "but they converge on similar cellular processes associated with neural signaling and neural connectivity, and are functionally validated at a high rate."
Also in PNAS, an international research group led by investigators at the US Department of Energy Joint Genome Institute, the University of California, Berkeley, and the Pasteur Institute reported on efforts to flesh out cyanobacterial phylogeny through genome sequencing on carefully chosen strains.
The investigators performed whole genome sequencing on 54 cyanobacterial strains, selected with an eye to maximizing phylogenetic and phenotypic diversity, and generated 29 complete new cyanobacterial genomes and another 25 draft genomes. With the resulting "CyanoGEBA" dataset — so named as a nod to the Genomic Encyclopedia of Bacteria and Archaea, or GEBA, project that inspired the phylogenetics-focused strain selection — researchers identified a slew of new predicted protein-coding genes and uncovered some of the molecular features underlying the varied and complex features found in the cyanobacterial tree.
"The extensive phylogenetically based survey of this single phylum has refined and extended our understanding of plastid evolution, phenotypic differences in morphology, light-harvesting complexes, and secondary metabolisms in cyanobacteria," study leaders Cheryl Kerfeld with JGI and Muriel Gugger from the Pasteur Institute and their co-authors wrote, adding that the study "demonstrates the benefits gained from a more balanced representation of sequenced genomes within a phylum."
A new computational approach has been showing promise for assessing the accuracy of genome assemblies produced with a wide range of assemblers, according to a study in PLOS One by investigators in the US and Italy.
The approach relies on assessments of a core set of statistical features within genome assemblies, the team explained, using a combination of principal component analyses, independent component analyses, machine learning, and other methods to get at information on genome structures present prior to error-correction and other assembly steps. As such, the method extends a previous tactic for looking at assembly quality and accuracy, known as the Feature Response Curve, the study's authors noted, explaining that "by focusing on a reduced set of highly informative features we can use the FRC curve to better describe and compare the performances of different assemblers."
"As a consequence of our analysis," they added, "we can highlight the differences between the synthetic features obtained from real data sets versus the ones obtained from simulated datasets, and thus, gauge reliability of empirical analyses based on simulated data."
A Singapore-based research team that has its sights set on generating relatively deep whole-genome sequence data on 50 female and 50 male individuals from Austronesian-speaking Malay populations in Singapore, Malaysia, and Indonesia presented progress on this project in the American Journal of Human Genetics.
Members of the Singapore Sequencing Malay Project, or SSMP, reported that they have now sequenced 96 Malay genomes to depths of at least 30-fold average coverage apiece, identifying some 14 million new SNPs, around 1.6 million small insertions or deletions, and tens of thousands of larger deletions. With the new genome sequence data in hand, the team also looked at questions related to Malay population structure and relationships to neighboring populations as well as the rare and low frequency genetic variant patterns in Malays. Moreover, they reported, the work offered a peek at sites in the genome that appear prone to mutations with functional significance — such as loss-of-function changes — in Malay individuals and in the population as a whole.
"The SSMP data are expected to be the benchmark for evaluating the value of deep population-level sequencing versus low-pass sequencing," the National University of Singapore's Yik-Ting Teo and colleagues wrote, "especially in populations that are poorly represented in population-genetics studies."
Genomics In The Journals is a weekly feature pointing readers to select, recently published articles involving genomics and related research.